Tıbbi Bilişim ve Sistemler

ARAŞTIRMACILAR

Unvanı	Adı – Soyadı	Kurum	Fakülte	Bölüm
Prof. Dr.	Tamer Ölmez	İstanbul Teknik Üniversitesi	Elektrik-Elektronik Fakültesi	Elektronik ve Haberleşme Müh.
Y.Doç.Dr.	Berat Doğan	İnönü Üniversitesi	Mühendislik Fakültesi	Biyomedikal Müh.
Prof. Dr.	Zümray Dokur Ölmez	İstanbul Teknik Üniversitesi	Elektrik-Elektronik Fakültesi	Elektronik ve Haberleşme Müh.
Doç.Dr.	Hüseyin Şeker	İngiltere North Umbria Universitesi		Computer and Information Science
Prof. Dr.	Nizamettin Aydın	Yıldız Teknik Üniversitesi	Elektrik-Elektronik Fakültesi	Bilgisayar Müh.
Y.Doç.Dr.	Yücel Koçyiğit	Manisa Celal Bayar Üniversitesi	Mühendislik Fakültesi	Elektrik-Elektronik Müh.
Prof. Dr.	Hakkı Oktay Seymen	İstanbul Üniversitesi	CerrahpaşaTıp Fakültesi	Fizyoloji
Dr.	Zafer İşcan	National Research University- Russian	higher school of economics	higher school of economics
Prof. Dr.	Mustafa Yıldız	İstanbul Üniversitesi	Kardiyoloji Enstitüsü	Kardiyoloji Kliniği
Prof. Dr.	Ata Akın	Acıbadem Üniversitesi	Mühendislik Fakültesi	Tıp Mühendisliği
Prof.Dr.	Mustafa Bağrıyanık	İTÜ	Elektrik-Elektronik Fakültesi	Elektrik Müh. Bölümü
Y .Doç.Dr.	Özlem Polat	Cumhuriyet Üniversitesi	Teknoloji Fak.	Mekatronik Müh.

Mecvut Laboratuvar İmkanları

Cihazlar	Modeller
Polygraph sistemi ve modüler üniteler	NIHON KOHDEN - RM 6000
Microboard Sistemi (Training System)	80286
Dinamik Köprü	ABM AE 02 A
13 MHz Function Generator	BK Precision 3040
Triple Output Power Supply	BK Precision I660
Multifunction I / O Card	BYTRONIC
Transducer & Instrumentation Trainer	DIGIAC 1750
Microprocessor System	DIGIAC 2000
Protoboard Çalışma Seti	E & L Instruments - ADAM 5005
Board	E & L Instruments - CADET
Circuit Design Aid	GLOBAL - CDA-1
Protoboard Design Station	GLOBAL - Protoboard PB 88/4
100 MHz Oscilloscope	GOULD DSO 465
50 MHz Universal Counter	HP 5302A
Oscillator	LEVELL TG152DM RC
Function Generator	SCHLUMBERGER SG-1271
Master Builder	SCIENCE Instruments Co. S3008
Four Channel Oscilloscope	TEKTRONIX TAS 475
20 MHz Function Generator	THANDAR TG2001
Universal Counter	THURLBAY / THANDAR TF830
TRANSPUTER Train System (4'lü)	TRANSPUTER
Spectophotometer	WPA S105
16-Kanal EEG kayıt sistemi	V- Amp Brain Vision
Sanal Gözlük	Sony PLM-S700E (Glasstron)
Hareket algılayıcısı (6 serbestiyet)	Polhemus InsideTrak
Sanal eldiven	5th Glove (5DT)
Geliştirme kiti	ST7 MCU ailesi
Geliştirme kiti	Texas Instruments (TMS320C3X)
Çok kanallı EKG sistemi	BIOPAC MP36 veri toplama sistemi
Osiloskop	GWINSTEK 2 KANAL 250 MHz
İzolasyon Ölçüm Cihazı	BIO-TEK - 501 PRO
Blood Pressure Systems Calibrator	BIO-TEK - 601A
Defibrillator Analyser	BIO-TEK - QED-4
Electrosurgery Analyser	BIO-TEK - RF-302
Ultrasound Wattmeter	BIO-TEK - UW-11
Infusion Device Analyser	BIO-TEK Instruments - IDA-1
Multiparameter ECG Simulator	BIO-TEK Lionheart

Başlıca Çalışmalar ve Projeler

1) Biyolojik İşaretlerin (EKG, EMG, vb.) İşlenmesi

2) Bilgisayar Desteği ile Biyolojik İşaretlerin Yorumlanması ve Tanınması

3) Biyomedikal Görüntü İşleme ve Hastalık Teşhisine Destek

4) Medikal Görüntüleme: Manyetik Rezonans, Bilgisayarlı Tomografi,

Radyonüklid, Ultrasonik Görüntüleme Teknikleri

5) Medikal Kesit Görüntülerinden Üç Boyutlu Görüntü Oluşturma (3B Görselleştirme)

6) Tıpta Sanal Gerçeklik

7) Medikal Bilişim, Tele-sağlık

8) Biyomedikal İşaretlerin İletilmesi, Dağıtılması

9) Yapay Zeka ile Hastalık Teşhisine Destek

10) Makina Öğrenmesi (Yapay Sinir Ağları, Genetik Algoritmalar, Bulanık Mantık)

11) Tıpta Bilgisayar Destekli Sistem Tasarımı

12) Yapay Organ ve Protez Kontrolü

13) Gerçek Zamanda Sistem Tasarımı

14) Ultrasonik Görüntüleme

15) Veri Madenciliği

16) Biyolojik Sistemlerin Modellenmesi

17) Beyin – Bilgisayar Arayüzü Tasarımı

18) Elektroensefalogram Kullanılarak Beynin Çalışmasının Analizi

19) Medikal Enstrumantasyon

Ticarileşen, Ticarileşme Aşamasında olan veya Ticarileşme Potansiyeli olan Ürünler:

1) Telsiz ortamda biyolojik işaretlerin internet üzerindeki bir sunucuya gönderilmesi

Geliştirilen Başlıca Yöntemler, Prosedürler, Mekanizmalar, Ürünler, Yönetmelikler:

YAYINLAR

Prof. Dr. Tamer Ölmez

Yayın

[1] Yüksel A., Ölmez T., A Neural Network-Based Optimal Spatial Filter Design Method for Motor Imagery Classification, PLOS-ONE, DOI: 10.1371/journal.pone.0125039, 2015.

[2] Dogan, B., Ölmez, T., Vortex search algorithm for the analog active filter component selection problem, AEU-INTERNATIONAL JOURNAL OF ELECTRONICS AND COMMUNICATIONS, vol 69., issu. 9, 2015.

[3] Berat Doğan, Tamer Ölmez, A novel state space representation for the solution of 2D-HP protein folding problem using reinforcement learning methods, Applied Soft Computing, Volume 26, January 2015, Pages 213-223, ISSN 1568-4946,http://dx.doi.org/10.1016/j.asoc.2014.09.047.

[4] Berat Doğan, Tamer Ölmez, A new metaheuristic for numerical function optimization: Vortex Search algorithm, Information Sciences, Volume 293, 1 February 2015, Pages 125-145, ISSN 0020-0255, http://dx.doi.org/10.1016/j.ins.2014.08.053.

[5] M. Korürek, A. Yüksel, Z. Iscan, Z. Dokur, T. Ölmez, “Retrospective correction of near field effect of X-ray source in radiographic images by using genetic algorithms”, Expert Systems with Applications, accepted 2009

[6] M. Korürek, A. Yüksel, Z. Dokur, T. Ölmez, “Dimension reduction by a novel unified scheme using divergence analysis and genetic search”, Digital Signal Processing, accepted 2009.

[7] Z. Iscan, Z. Dokur, T. Ölmez, “Tumor detection by using Zernike moments on segmented magnetic resonance brain images”, Expert Systems with Applications, doi:10.1016/j.eswa.2009.08.003, 2009.

[8] Z. Iscan, A. Yüksel, Z. Dokur, M. Korürek, T. Ölmez “Medical image segmentation with transform and moment based features and incremental supervised neural network”, Digital Signal Processing, vol.19, no. 5, pp. 890-901, 2009.

[9] Z. Dokur, T. Ölmez, “Feature determination for heart sounds based on divergence analysis”, Digital Signal Processing, vol. 19, no. 3, pp. 521-531, 2009.

[10] Z. Dokur, T. Ölmez, “Heart sound classification using wavelet transform and incremental self-organizing map”, Digital Signal Processing, vol. 18, no. 6, pp. 951-959, 2008.

[11] Z. Dokur, T. Ölmez, “Tissue segmentation in ultrasound images by using genetic algorithms”, Expert Systems with Applications, vol.34, no.4, pp.2739–2746, 2008.

[12] M.N. Kurnaz, Z. Dokur, T. Ölmez, “An incremental neural network for tissue segmentation in ultrasound images”, Computer Methods and Programs in Biomedicine, vol. 85, no. 3, pp. 187-195, 2007.

[13] Z. Dokur, Z. Iscan, T. Ölmez, “Segmentation of medical images by using wavelet transform and incremental self-organizing map”, Lecture Notes in Artificial Intelligence LNAI 4293, pp. 800-809, 2006.

[14] M.N. Kurnaz, Z.Dokur, T Ölmez, “Segmentation of remote-sensing images by incremental neural network”, Pattern Recognition Letters, vol.26, no. 8, pp. 1096-1104, 2005.

[15] Z. Dokur, T. Ölmez, “Classification of respiratory sounds by using an artificial neural network”, International Journal of Pattern Recognition and Artificial Intelligence IJPRAI, vol. 17, no. 4, pp. 567-580, 2003.

[16] Z. Dokur, T. Ölmez, “Segmentation of MR and CT images by using a quantiser neural network”, Neural Computing & Applications, vol. 11, no. 3-4,pp. 168-177, 2003.

[17] T. Ölmez, Z. Dokur, “Application of InP neural network to ECG beat classification”, Neural Computing & Applications, vol. 11, no. 3-4,pp. 144-155, 2003.

[18] T. Ölmez, Z. Dokur, “Classification of heart sounds using an artificial neural network”, Pattern Recognition Letters, vol. 24, no. 1-3, pp. 617-629, 2003.

[19] Z. Dokur, T. Ölmez, “Segmentation of ultrasound images by using a hybrid neural network”, Pattern Recognition Letters, vol. 23, no. 14, pp. 1825-1836, 2002.

[20] Z. Dokur, T. Ölmez, “ECG beat classification by a novel hybrid neural network”, Computer Methods & Programs in Biomedicine, vol. 66, pp. 167-181, 2001.

[21] Z. Dokur, T. Ölmez, E. Yazgan, “Comparison of discrete wavelet and Fourier transforms for ECG beat classification”, Electronics Letters, vol. 35, no. 18, pp. 1502-1504, 1999.

[22] T. Ölmez, “Classification of ECG waveforms by using RCE neural network and genetic algorithms”, Electronics Letters, vol. 33, no. 18, pp. 1561-1562, 1997.

[23] Z. Dokur, T. Ölmez, E. Yazgan, O.K. Ersoy, “Detection of ECG waveforms by neural networks”, Medical Engineering & Physics, vol. 19, no. 8, pp. 738-741, 1997.

[24] T. Ölmez, E. Yazgan, O. K. Ersoy, “A multilayer incremental neural network architecture for classification”, Neural Processing Letters, vol.2, no. 2, pp. 5-9, 1995.

[25] T. Ölmez, E. Yazgan, O. K. Ersoy, “Optimized competitive feature vector network”, Electronics Letters, vol. 30, no. 24, pp. 2052-2053, 1994.

[26] T. Ölmez, E. Yazgan, O. K. Ersoy, “Modified restricted Coulomb energy neural network”, Electronics Letters, vol. 29, no. 22, pp. 1963-1965, 28 Oct. 1993.

Tamamlanmış Y.Lisans Tezleri

[1] Basri Erdoğan, “Fonksiyonel Manyetik Rezonans Görüntüleme İle Eş Zamanlı Kaydedilen Elektroensefalogram Üzerinde Oluşan Artefaktların Giderilmesi”, Istanbul Technical University, Institute of Science and Technology, May 2009.

[2] Bora Cebeci, “Elektroensafalografi İle Anestezi ve Sedasyon Düzeyinin İlinti Boyutu ve Dalgacık Faz Uyumu Analizi”, Istanbul Technical University, Institute of Science and Technology, January 2009.

[3] Ayhan Yüksel, “X-Işını El Görüntülerinde Kemik Dokusunun Bölütlenmesi”, Istanbul Technical University, Institute of Science and Technology, 2008.

[4] Zafer İşcan, “Yapay Sinir Ağları Kullanarak Ultrasonik Görüntülerde Dokuların Bölütlenmesi”, Istanbul Technical University, Institute of Science and Technology, 2005.

[5] Ali Katkar, “Biyomedikal Görüntülerin Dalgacık Dönüşümü ile Sıkıştırılması”, Istanbul Technical University, Institute of Science and Technology, 2002.

[6] Güray Güngör, “Gevşeme Temelli Kenar Belirleme Algoritması”, Istanbul Technical University, Institute of Science and Technology, 1998.

Tamamlanmış Doktora Tezleri

[1] Zümray Dokur, "Yapay Sinir Ağları ve Genetik Algoritmalar Kullanılarak EKG Vurularının Sınıflandırılması", Istanbul Technical University, Institute of Science and Technology, 27 January 2000.

[2] Mehmet Nadir Kurnaz, "Ultrasonik ..", Istanbul Technical University, Institute of Science and Technology, 2007.

Prof. Dr. Mehmet Korürek

Yayın

[1] M. Korürek, A. Yüksel, Z. Iscan, Z. Dokur, T. Ölmez, “Retrospective correction of near field effect of X-ray source in radiographic images by using genetic algorithms”, Expert Systems with Applications, vol.37, no. 3, pp. 1946-1954, 2010.

[2] M. Korürek, A. Yüksel, Z. Dokur, T. Ölmez, “Dimension reduction by a novel unified scheme using divergence analysis and genetic search”, Digital Signal Processing, accepted 2009.

[3] Z. Iscan, A. Yüksel, Z. Dokur, M. Korürek and T. Ölmez, "Medical image segmentation with transform and moment based features and incremental supervised neural network", Elsevier, Digital Signal Processing, (2009), In press.

[4] B. Karlık, Y. Koçyigit and M. Korürek, "Differentiating types of muscle movements using a wavelet based fuzzy clustering neural network", Blackwell Publ., Expert Systems, The Journal of Knowledge Engineering, vol 26 no 1, (2009), 49-59.

[5] M. Korürek, A. Nizam, "A new arrhythmia clustering technique based on Ant Colony Optimization", Elsevier, Journal of Biomedical Informatics 41, (2008), 874-881.

[6] M. Engin, M. Fedekar, E. Z. Engin and M. Korürek, "Feature measurements of ECG beats based on statistical classifiers", Elsevier, Measurement 40, (2007), 904-912.

Tamamlanmış Yüksek Lisans Tezleri

[1] Doğan, B., Parçacık Sürü Optimizasyonuna Dayalı Yeni Bir Aritmi Sınıflama Yöntemi, Haziran 2009.

[2] Karadağ, A., Dalgacık Ağlarıyla Elektrokardiyografik Aritmilerin sınıflandırılması, İTÜ. Fen Bilimleri Enstitüsü, Mayıs 2009.

[3] Çırak, T., Mikroişlemci Tabanlı Biyolojik Veri Toplama Sistemi,İTÜ-FBE, Eylül 2009.

[4] Özkaya, A., A new approach for the epilepsy diagnosis and for the localization of epileptogenic brain regions, İTÜ. Fen Bilimleri Enstitüsü, December 2007.

[5] Karakaş, S., Devoloping techniques for reducing EMC effect on microcontroller based medical equipment, İTÜ. Fen Bilimleri Enstitüsü, Mayıs 2007.

[6] Kuzu, E. A., Dilsizler için konuşmaya yardımcı sistemler, İTÜ. Fen Bilimleri Enstitüsü, 2006.

[7] Kaynakçı, M., Ş., Ters iyontoforez yöntemiyle non-invazif kan şekeri ölçümü, İTÜ. Fen Bilimleri Enstitüsü, Mayıs 2006.

[8] Şengil, E., Beyin Bilgisayar Arayüzü (BCI), İTÜ. Fen Biliml. Enstitüsü, Mayıs 2004.

[9] Meşe, M., Hasta Kayıt Sistemi, İTÜ. Fen Bilimleri Enstitüsü, Mayıs 2003.

[10] Metin, S., Elektrokardiyogram vuruşlarının gal ağı yardımıyla sınıflandırılması, İTÜ. Fen Bilimleri Enstitüsü, Mayıs 2003.

[11] Şeker, H. A., Hilbert transformundan yararlanarak EKG işaretlerinin analizi ve sınıflaması, İTÜ. Fen Bilimleri Enstitüsü, Nisan 2002.

[12] Buran, R., Fizik tedavi yöntemleri ve mikrodenetleyicili TENS tasarımı, İTÜ-FBE, 2002.

[13] İnce, O., Sayısal konrollu çok kanallı işitme cihazı tasarımı, İTÜ-FBE, 2002.

[14] Sezgin, M. C., Solunum Seslerinin Sayısal Olarak Kaydedilmesi, Analizi ve Sınıflandırılması, İTÜ. Fen Bilimleri Enstitüsü, Nisan 2000.

[15] Nizam, M., Mikrodenetleyici kontrollu çok kanallı elektrokardiyografi cihazı tasarımı, İTÜ. Fen Bilimleri Enstitüsü, 2000.

[16] Nizam, A., EKG işaretlerini gerçek zamanda bilgisayara aktaran ve işleyen arayüz programı tasarımı, İTÜ. Fen Bilimleri Enstitüsü, 2000.

[17] Kırcı, H., Kardiyovasküler sistemin modellenmesi, İTÜ-FBE, 1999.

[18] Baki, C., Elektrokardiyografik işaretlerin Yarkar ve Tablo temelli Yarkar yöntemleriyle sıkıştırılması, İTÜ-FBE, 1998.

[19] Köroğlu, M., Elektrokardiyografik İşaretlerde QRS Deteksiyon Algoritmaları, İTÜ. Fen Bilimleri Enstitüsü, Haziran 1996.

[20] Özenç, S., Sözdizimi Metodu İle Elektrokardiyografi İşaretlerinin Analizi, İTÜ. Fen Bilimleri Enstitüsü, Ocak 1996.

[21] Koçyiğit, Y., Yapay Sinir Ağları Kullanılarak EKG Verilerinin Sıkıştırılması, İTÜ. Fen Bilimleri Enstitüsü, Ocak 1996.

[22] Aktaner, A., Entropi Kodlama İle EKG Veri Sıkıştırması, İTÜ. Fen Bilimleri Enstitüsü, Haziran 1995.

[23] Şeker, H., Elektromiyografik İşaretlerin Bulanık Sınıflayıcılarla Sınıflandırılması, İTÜ. Fen Bilimleri Enstitüsü, Haziran 1995.

[24] Dokur, Z., Bulanık (Fuzzy) Sınıflayıcılarla EKG Şekil Bozukluklarının Belirlenmesi, İTÜ. Fen Bilimleri Enstitüsü, Ocak 1995.

[25] Hız, H., Homomorfik Filtreleme İle EKG Analiz, İTÜ. Fen Bilimleri Enstitüsü, Haziran 1995.

[26] Uygun, T., Uzaktan Algılanan Biyolojik İşaretlerin Modem Yardımıyla Bilgisayara Aktarılması, İTÜ. Fen Bilimleri Enstitüsü, Ocak 1995.

[27] Etçibaşı, T., Kartlı Aktif Elektrik Enerjisi Sayaç Sistemi, İTÜ. Fen B Enstitüsü, 1994.

[28] Özkaptan, S., Biyotelemetri Sistemi, İTÜ. Fen Bilimleri Enstitüsü, Ocak 1994.

[29] Haşimi, İ., Doppler Kan Akış Hızı İşaretlerinin Güç Spektrum Analizleri, İTÜ. Fen Bilimleri Enstitüsü, Haziran 1994.

[30] Tormaç, T., Empedans Pletismografisi Yöntemiyle Kan Akış Hacminin ve Kalbin Fizyolojik Parametrelerinin Bilgisayar Destekli Ölçümü, İTÜ. Fen Bilimleri Enstitüsü, Haziran 1993.

[31] Alanyalı, G., Otomatik Aritmi Dedeksiyonu, İTÜ. Fen Bilimleri Enstitüsü, Temmuz 1993.

[32] Savran, A., Görsel Uyarılmış Potansiyellerin Kalman Süzgeci İle Kestirimi, İTÜ. Fen Bilimleri Enstitüsü, Eylül 1993.

[33] Sezen, C., Genel Amaçlı Biyopotansiyel Kuvvetlendirici, İTÜ. Fen Bilimleri Enstitüsü, Temmuz 1992.

[34] Alper, C., Kan Hücre Sayıcılarının İncelenmesi ve Beyaz Kan Hücrelerinin Elektronik Devre Yardımıyla Analizi, İTÜ. Fen Bilimleri Enstitüsü, 1992.

[35] Şamlı, Ö. T., Görsel Uyarılmış Potansiyellerin Optimal Filtrelenmesi, İTÜ. Fen Bilimleri Enstitüsü, Nisan 1992.

[36] Dilmaç, S., 8031 Mikrodenetleyici Kontrolunun Biyomedikalde Uygulamaları, EKG Aritmi Detektörü, İTÜ. Fen Bilimleri Enstitüsü, 1992.

[37] Oktay, O., Biyolojik İşaretlerin Elde Edilip İşlenmesi, İTÜ. Fen Bilimleri Enstitüsü, Ağustos 1991.

[38] Evin, M., Veri Azaltma Tekniklerinin Elektrakardiyografi İşaretlerine Uygulanması, İTÜ. Fen Bilimleri Enstitüsü, 1991.

[39] Molak, S., İki Kanallı Elektrokardiyografik Monitoru, İTÜ. Fen Bilimleri Enstitüsü, Haziran 1991.

[40] Hanef, M., Yapay Zeka Yaklaşımına Dayalı Bir Tıbbi Teşhis Programı, İTÜ. Fen Bilimleri Enstitüsü, İTÜ. Fen Bilimleri Enstitüsü, 1991.

[41] Kuyucu, Ö., Elektromiyografik İşaretlerin Değerlendirilmesi, İTÜ. Fen Bilimleri Enstitüsü, İTÜ. Fen Bilimleri Enstitüsü, 1989.

[42] Karaağaç, S., EMG İşaretlerine Ait Bazı Parametrelerin PC Yardımıyla Bulunması, İTÜ. Fen Bilimleri Enstitüsü, 1989.

Tamamlanmış Doktora Tezleri

[1] Koçyiğit, Y., Çok Fonksiyonlu Kol Protezleri İçin EMG İşaret İşleme Sistemi, İTÜ. Fen Bilimleri Enstitüsü, Ocak 2004.

[2] Nizam, A., Karınca Koloni Optimizasyonuna Dayalı Yeni Bir Aritmi Sınıflama Tekniği, İTÜ. Fen Bilimleri Enstitüsü, Eylül 2008.

Prof. Dr. Zümray Dokur Ölmez

Yayın

[1] M. Korürek, A. Yüksel, Z. Iscan, Z. Dokur, T. Ölmez, “Retrospective correction of near field effect of X-ray source in radiographic images by using genetic algorithms”, Expert Systems with Applications, vol.37, no. 3, pp. 1946-1954, 2010.

[2] M. Korürek, A. Yüksel, Z. Dokur, T. Ölmez, “Dimension reduction by a novel unified scheme using divergence analysis and genetic search”, Digital Signal Processing, accepted 2009.

[3] Z. Iscan, Z. Dokur, T. Ölmez, “Tumor detection by using Zernike moments on segmented magnetic resonance brain images”, Expert Systems with Applications, vol.37, no. 3, pp. 2540-2549, 2010.

[4] Z. Iscan, A. Yüksel, Z. Dokur, M. Korürek, T. Ölmez “Medical image segmentation with transform and moment based features and incremental supervised neural network”, Digital Signal Processing, vol.19, no. 5, pp. 890-901, 2009.

[5] Z. Dokur, “Respiratory sound classification by using an incremental supervised neural network”, Pattern Analysis & Applications, doi:10.1007/s10044-008-0125-y, vol. 12, no. 4, pp. 309-319, 2009.

[6] Z. Dokur, T. Ölmez, “Feature determination for heart sounds based on divergence analysis”, Digital Signal Processing, vol. 19, no. 3, pp. 521-531, 2009.

[7] Z. Dokur, T. Ölmez, “Tissue segmentation in ultrasound images by using genetic algorithms”, Expert Systems with Applications, vol.34, no.4, pp.2739–2746, 2008.

[8] Z. Dokur, “A unified framework for image compression and segmentation by using an incremental neural network”, Expert Systems with Applications, vol. 34, no. 1, pp. 611-619, 2008.

[9] Z. Dokur, T. Ölmez, “Heart sound classification using wavelet transform and incremental self-organizing map”, Digital Signal Processing, vol. 18, no. 6, pp. 951-959, 2008.

[10] M.N. Kurnaz, Z. Dokur, T. Ölmez, “An incremental neural network for tissue segmentation in ultrasound images”, Computer Methods and Programs in Biomedicine, vol. 85, no. 3, pp. 187-195, 2007.Í

[11] M.N. Kurnaz, Z.Dokur, T Ölmez, “Segmentation of remote-sensing images by incremental neural network”, Pattern Recognition Letters, vol.26, no. 8, pp. 1096-1104, 2005.Í

[12] Z. Dokur, T. Ölmez, “Classification of respiratory sounds by using an artificial neural network”, International Journal of Pattern Recognition and Artificial Intelligence IJPRAI, vol. 17, no. 4, pp. 567-580, 2003.Í

[13] Z. Dokur, T. Ölmez, “Segmentation of MR and CT images by using a quantiser neural network”, Neural Computing & Applications, vol. 11, no. 3-4, pp. 168-177, 2003.Í

[14] T. Ölmez, Z. Dokur, “Application of InP neural network to ECG beat classification”, Neural Computing & Applications, vol. 11, no. 3-4, pp. 144-155, 2003. Í

[15] T. Ölmez, Z. Dokur, “Classification of heart sounds using an artificial neural network”, Pattern Recognition Letters, vol. 24, no. 1-3, pp. 617-629, 2003. Í

[16] Z. Dokur, “Segmentation of MR and CT images using a hybrid neural network trained by genetic algorithms”, Neural Processing Letters, vol. 16, no. 3, pp 211-225, 2002. Í

[17] Z. Dokur, T. Ölmez, “Recursive form of the discrete Fourier transform for two-dimensional signals”, Lecture Notes in Computer Science LNCS 2412, pp. 551-556, 2002. Í

[18] Z. Dokur, T. Ölmez, “Segmentation of ultrasound images by using a hybrid neural network”, Pattern Recognition Letters, vol. 23, no. 14, pp. 1825-1836, 2002. Í

[19] Z. Dokur, T. Ölmez, “ECG beat classification by a novel hybrid neural network”, Computer Methods & Programs in Biomedicine, vol. 66, pp. 167-181, 2001. Í

[20] Z. Dokur, T. Ölmez, E. Yazgan, “Comparison of discrete wavelet and Fourier transforms for ECG beat classification”, Electronics Letters, vol. 35, no. 18, pp. 1502-1504, 1999. Í

[21] Z. Dokur, T. Ölmez, E. Yazgan, O.K. Ersoy, “Detection of ECG waveforms by neural networks”, Medical Engineering & Physics, vol. 19, no. 8, pp. 738-741, 1997.

Tamamlanmış Y. Lisans Tezleri

[1] Özgür Say "Kalp Seslerinin Analizi ve Yapay Sinir Ağları ile Sınıflandırılması"(in Turkish), Istanbul Technical University, Institute of Science and Technology, June 2002.

[2] Özgün Onat Düzgün "Kalp Seslerinin Gerçek Zamanda Algılanması ve Bilgisayarda Analiz Edilmesi"(in Turkish), Istanbul Technical University, Institute of Science and Technology, January 2007.

[3] Ali Fersak "MR Kafa Görüntülerinde Tümör Deteksiyonu İçin Simetri Temelli Parametrelerin Belirlenmesi"(in Turkish), Istanbul Technical University, Institute of Science and Technology, August 2007.

[4] Mustafa Yamaçlı "Fonokardiyogram Kayıtlarındaki S1-S2 Seslerinin Dalgacık Enerjileri ile Bölütlenmesi"(in Turkish), Istanbul Technical University, Institute of Science and Technology, June 2008.

Doktora Tezleri

[1] Zafer İşcan, Devam Ediyor, “EEG kullanılarak Beyin Arayüzünün Gerçeklenmesi”.

Prof. Dr. Ata Akın

Yayın

[1] Omer Sayli , Ertugrul Burtecin Aksel , Ata Akin, “Crosstalk and Error Analysis of Fat Layer on Continuous Wave Near-Infrared Spectroscopy Measurements”, J Biomed Optics, Nov/Dec 2008

[2] Koray Çiftçi, Bülent Sankur, Yasemin Kahya, Ata Akın, "Constraining the general linear model for sensible hemodynamic response function waveforms", Med. & Biol. Engr. & Compt., 46:779–787, 2008

[3] Koray Çiftçi, Bülent Sankur, Yasemin Kahya, Ata Akın, “Multilevel Statistical Inference from Functional Near Infrared Spectroscopy Data during Stroop Interference” IEEE Trans Biomed (55), 9, 2212-2220, 2008

[4] U E Emir, C Oztürk, A Akın, "Multimodal investigation of fMRI and fNIRS derived breath hold BOLD signals with an expanded balloon model", PHYSIOL. MEAS. 29 (1), 49-63, (2008)

[5] Tunahan Çakır, Selma Alsan, Hale Saybaşılı, Ata Akın, Kutlu Ö Ülgen, "Reconstruction and flux analysis of coupling between metabolic pathways of astrocytes and neurons: application to cerebral hypoxia" Theoretical Biology and Medical Modelling, 4:48, 2007

[6] Mustafa Dinler, Erdem Kaşıkçıoğlu, Ata Akın, Ömer Şayli, Cihan Aksoy, Ahmet Öncel, Ender Berker, “Exercise capacity and oxygen recovery half times of skeletal muscle in patients with fibromyalgia,” Rheumatol. Int. 27, 311-313, 2007

[7] Ceyhun B. Akgül, Ata Akın, Bülent Sankur, “Extraction of cognitive activity-related waveforms from functioncal near-infrared signals,” Med. & Biol. Compt. & Engr 2006, 44, 945-958

[8] Ata Akin, Didem Bilensoy, “Cerebrovascular reactivity to hypercapnia in migraine patients measured with near-infrared spectroscopy” Brain Research, (1107), 206-214, 2006

[9] Ata Akın, Didem Bilensoy, Uzay E. Emir, Murat Gülsoy, Selçuk Candansayar and Hayrunnisa Bolay, “Cerebrovascular dynamics in patients with migraine: Near-infrared spectroscopy study” Neuroscience Letters, (400), 86-91, 2006

[10] Erdem Kasikcioglu, Armagan Arslan, Berrin Topcu, Omer Sayli, Hulya Akhan, Huseyin Oflaz, Ata Akın, Abidin Kayserilioglu, Mehmet Meric, “Cardiac fatigue and oxygen kinetics after prolonged exercise” International Journal of Cardiology (108), 286-288, 2006

[11] Sinem Tiveci, A.Akın, T. Çakır, H. Saybaşılı, K. Ülgen, “Modeling of Calcium dynamics in brain energy metabolism and Alzheimer’s disease,” Computational Biology and Chemistry, 29 (2), 151-162, 2005

[12] Ceyhun Burak Akgül, Bülent Sankur, Ata Akın, “Spectral Analysis of Event-Related Hemodynamic Responses in Functional Near Infrared Spectroscopy”, Journal of Computational Neuroscience (18) 67-83, 2005.

[13] A.Akın and H. H. Sun “Non-invasive measurement of gastric motility with fast Electrogastrogram (fEGG)” Physiological Measurement, 23, 505–519, 2002

[14] A.Akın, H. H. Sun, “Time and Frequency Methods for Detecting Spike Activity of Stomach,” Med. & Biol. Engr. & Compt., vol. 37, pp. 381-390, 1999

Tamalanmış Y.Lisans Tezleri

[1] Cozmi, Michaela, “The use of dynamic light scattering as a noninvasive early diagnostic tool for cataracts : a feasibility study” Drexel University, Philadelphia, 2001

[2] Kim, Sanghyun, “Design of a handheld near-infrared (NIR) imager”, Drexel University, Philadelphia, 2001

[3] Emir, U., “System characterization for a fast optical imager,” Boğaziçi Üniversitesi, 2003,

[4] Çakıroğlu, M. “Functional near infrared spectroscopy as a tool for neuroimaging studies,” Boğaziçi Üniversitesi, 2003,

[5] Kacar, B. “Implementation of neurovascular coupling model to hyperammonemia” Boğaziçi Üniversitesi, Haziran 2004

[6] Yılmaz, O. “Applications of Microsphere Morphology Dependent Resonances to Biosensor Applications” Boğaziçi Üniversitesi, Haziran 2004

[7] Tiveci, S. “The role of calcium dynamics in brain energy metabolism”, Boğaziçi Üniversitesi, Ekim 2004

[8] Alsan, S. “The Stoichiometric coupling between astrocytes and neuron”, Boğaziçi Üniversitesi, Ocak 2005

[9] Özcan, K. “Noninvasive monitoring of gastric motility in humans”, Boğaziçi Üniversitesi, Ocak 2005

[10] Acar, B. “Implementation of a multi-parameter biomedical monitoring system,” Boğaziçi Üniversitesi, Ocak 2005

[11] Yücel, M. A. “A Biochemical Model For The Interactions Between Tumor Cell Mass And Vascular Epithelial Cells Leading To Angiogenesis” Boğaziçi Üniversitesi, Haziran 2005

[12] Fidan, M. “Finite Element modeling of photon migration in tissue” Boğaziçi Üniversitesi, Haziran 2005

[13] Yücetaş, A. “Quantification and modeling of muscle metabolism by near infared spectroscopy”, Boğaziçi Üniversitesi, Haziran 2005

[14] Karaca, S. “Wireless functional optical imager” Boğaziçi Üniversitesi, Haziran 2005

[15] Erdem, F. D. “Evaluation of quadriceps muscle endurance with functional near infrared specroscopy (fNIRS)” Boğaziçi Üniversitesi, Haziran 2005

[16] Bilensoy, D. “Cerebrovascular dynamics in migraineurs measured by fNIRS,” Boğaziçi Üniversitesi, Haziran 2005

[17] Alptekin, Z, “Measuring changes in cerebral oxygenation and hemodynamics during obstructive sleep apnea by functional near-infrared spectroscopy,” Haziran 2006

[18] Alkaş, E. “Quantification of the effect of warm up and stretching on the oxygen metabolism using an improved version of a fNIRS device” Ağustos 2006

[19] Şahin, B. “Effect of incident light intensity and source setector seperation on photon migration depth in turbid media” Haziran 2006.

[20] Taşdöğen, S. “Integrated Neurovascular Coupling (Nvc) Model: An fNIRS Study On Migraine” Mart 2007 (Eş-danışman)

[21] Topaloğlu, N. “The effect of methylphenidate on brain hemodynamics of attention-deficit/hyperactivity disorder measured by functional near infrared spectroscopy” Temmuz 2007

[22] Erdoğan, SB. “Evaluation of local oxygen consumption in human flexor digitorum suoerficialis muscle by near infrared spectroscopy” Eylül 2007

[23] Karahan, E. “An ARX model approach to fNIRS data acquired from migraine and healthy subjects” Eylül 2007

[24] Kara, E. “Subband filtering of fNIRS data from schizophrenic subjects” Ocak 2008

[25] Özkerim, B. “Fiber optic based continuous wave functional near infrared spectroscopy system” Mart 2008

[26] Kırımlı, C. E., “Working memory performance assessment while monitoring the prefrontal cortex hemodynamics by means of functional near infrared spectroscopy” Haziran 2008

[27] Nevşehirli, T. D. “Cerebrovascular reactivity of free divers measured with fNIRS” Ağustos 2008

[28] Kubat, E. “Evaluation of the effect of aging on brain asymmetry with functional near infrared spectroscopy,” Haziran 2008

[29] Ünlü, E. “Hemodynamic correlates of mental arithmetic task in migraine”,

[30] Evcil, K. “Optical probe design for continuous wave near-infrared spectroscopy”

[31] Serap, S. “Investigating brain hemodynamics of schizophrenic patients by functional near infrared spectroscopy”

Tamalanmış Doktora Tezleri

[1] Emir, U. “Multimodal Investigation of fMRI and fNIRS derived Breath Hold BOLD Signals with an Expanded Balloon Model,” Boğaziçi Üniversitesi, Ocak 2008 (mezun)

[2] Çiftçi, K. “Statistical analysis of cognitive signals measured by fNIRS,” Boğaziçi Üniversitesi Haziran 2008 (mezun)

[3] Şayli, Ö. “Muscle Metabolism Measurement in health and disease by fNIRS,” Boğaziçi Üniversitesi, Kasım 2009 (mezun)

[4] Aksel, B. “Optimal probe geometry in functional near infrared spectroscopy” Boğaziçi Üniversitesi, Haziran 2010

[5] Yücel, MA. “Expanded Neurovascular coupling model” Şubat 2010

Prof. Dr. Nizamettin Aydın

Yayın

[1] Bale K, Chapman P, Barraclough N, Purdy J, Aydin N, and Dark P, "Kaleidomaps: a new technique for the visualization of multivariate time-series ". Information Visualization, Vol. 6; No. 2, 155-167, 2007.

[2] Temel T, Morgul A, and Aydin N, " A novel signed higher-radix full-adder algorithm and implementation with current-mode multi-valued logic circuits ". IEE Proc.-Circuits Devices Syst., Vol. 153, No. 5, 489-496, October 2006.

[3] Aydin N, Arslan T, Cumming DRS, "A Direct Sequence Spread-spectrum Communication System for Integrated Sensor Microsystems". IEEE Trans Inf Tech Biomed. 9, 1, 4-12, 2005.

[4] Aydin N, Marvasti F, Markus HS, "Embolic Doppler ultrasound signal detection using discrete wavelet transform". IEEE Trans Inf Tech Biomed. 8, 2, 182-190, 2004.

[5] Seker H, Evans DH, Aydin N, Yazgan E, "Compensatory fuzzy neural network based intelligent detection of abnormal neonatal cerebral Doppler ultrasound waveforms". IEEE Trans Inf Tech Biomed. 5, 3, 187-194, 2001.

[6] Aydin N, Markus HS, "Time-scale analysis of quadrature Doppler ultrasound signals". IEE Proceedings - Science, Measurement and Technology. 148, 1, 15- 22, 2001.

[7] Aydin N, Markus HS, "Directional wavelet transform in the context of complex quadrature Doppler signals". IEEE Signal Processing Letters. 10, 7, 278-280, 2000.

[8] Aydin N, Markus HS, "Optimisation of processing parameters for the analysis and detection of embolic signals". European Journal of Ultrasound. 12, 1, 69-79, 2000.

[9] Aydin N, "Time varying filtering approach for simulation of ultrasonic Doppler signals". Journal of Computer Simulation & Modelling in Medicine. 1, 1, 67-76, 2000.

[10] Aydin N, Padayachee S, Markus HS, "The use of the wavelet transform to describe embolic signals". Ultrasound Med Biol. 25, 6, 953-958, 1999.

[11] Aydin N, Markus HS, "The use of the wavelet transform to describe embolic signals". Cerebrovasc Dis. 9, supl. 2, S7, 1999.

[12] Moraes R, Aydin N, Evans DH, "The performance of three maximum frequency envelope detection algorithms for Doppler signals". Journal of Vascular Investigation. 1, 3, 126-134, 1995.

[13] Aydin N, Evans DH, "A computerised arterial graft monitoring system". Journal of Vascular Investigation. 1, 2, 68-74, 1995.

[14] Thrush AJ, Aydin N, Nydahl S and Evans DH, "A new on - line automated system for monitoring lower limb bypass grafts". Journal of Ultrasound in Medicine, 14, supl. 3, S35, March 1995.

[15] Aydin N, Fan L, Evans DH, "Quadrature-to-directional format conversion of Doppler signals using digital methods". Physiol Meas, 15, 181-199, 1994.

[16] Aydin N, Evans DH, "Implementation of directional Doppler techniques using a digital signal processor". Med Biol Eng Comput, 32, S157-S164, 1994.

Prof. Dr. Bekir Karlık

Yayın

[1] BUCAK İ. Ömür and KARLIK Bekir, “Hazardous Odor Recognition by CMAC Based Neural Networks”, Sensors 2009, 9(9), 7308-7319; doi:10.3390/s90907308.

[2] KIZILASLAN Recep and KARLIK Bekir, “Comparison Neural Networks Forecasters for Monthly Natural Gas Consumption Prediction”, Neural Network World, 19 (2): 191-199, 2009.

[3] OKATAN Ali, KARLIK Bekir, DEMIREZEN Fatma, “Detection of Retinopathy Diseases Using Artificial Neural Network Based on Discrete Cosine Transform”, Neural Network World, Neural, 19 (2): 215-221, 2009.

[4] CEYLAN Rahime, OZBAY Yuksel, KARLIK Bekir, “A Novel Approach for Classification of ECG Arrhythmias: Type-2 Fuzzy Clustering Neural Network”, Expert Systems with Applications vol. 36, issue. 3, part.2, 6721-6726, April, 2009.

[5] KARLIK Bekir, AVCI Alpaslan, YABANIGÜL A. Talha, “Classification of Helicobacter Pylori According to National Strains Using Bayesian Learning”, Mathematical & Computational Applications, vol. 14, No. 3, pp.241-251, 2009.

[6] KARLIK Bekir, KORUREK Mehmet, KOCYIGIT Yücel, “Differentiating Types of Muscle Movements Using Wavelet Based Fuzzy Clustering Neural Network”, Expert Systems, vol. 26, (1), pp. 49-59, February 2009.

[7] ISERI Ali and KARLIK Bekir, “An Artificial Neural Networks Approach on Automobile-Pricing”, Expert Systems with Applications, vol. 36, issue. 2, part. 1, 2155-2160, March 2009.

[8] PETEK Mustafa and KARLIK Bekir, “Determination of the Mutagenic Effects of Pollution by Ames and Neural Networks”, NATO-ASI, Sensors for Environment, Health and Security: Advanced Materials and Technologies, Springer-Verlag, pp. 443-450, 2009.

[9] ALKAN Ahmet, SAHIN Y. Güneri, KARLIK Bekir, “A Novel Mobile Epilepsy Warning System”, Lecture Notes in Artificial Intelligence, 4304, 922 – 928, Springer-Verlag, 2006.

[10] KARLIK Bekir and YUKSEK Kemal “Fuzzy Clustering Neural Networks for Real Time Odor Recognition System”, Journal of Automated Methods and Management in Chemistry, Dec. 2007 Article ID 38405, doi:10.1155/2007/38405.

[11] TEMEL Turgay and KARLIK Bekir, “An Improved Odor Recognition System Using Learning Vector Quantization with a New Discriminant Analysis”, Neural Network World, 17 (4): 287-294 2007.

[12] B. Ayhan-SARAÇ, KARLIK Bekir, T. BALİ and T. AYHAN, “Neural Network Methodology for Heat Transfer Enhancement Data”, International Journal of Numerical Methods for Heat & Fluid Flow, vol.17, no:8, pp. 788 - 798, 2007.

[13] KARLIK Bekir, “Image Data Compression Using Vector Quantization Neural Network”, Neural Network World, 16 (4): 341-348 2006.

[14] H. Çetinel, H. Öztürk, E. Çelik, KARLIK Bekir, “Artificial Neural Network Based Prediction Technique for Wear Loss Quantities in Mo coatings”, Wear, 261 (10): 1064-1068, November, 30 2006.

[15] OZBAY Yuksel, PEKTATLI Rahime, KARLIK Bekir, “A Fuzzy Clustering Neural Network Architecture for Classification of ECG Arrhythmias”, Computers in Biology and Medicine, 36, pp.376–388, 2006.

[16] KARLIK Bekir, Uzam M., Cinsdikici M., and Jones A.H., “Neurovision-Based Logic Control of an Experimental Manufacturing Plant Using Convolutional Neural Net Le-Net5 and Automation Petri Nets”, Journal of Intelligent Manufacturing, vol. 16, No: 4-5, 527-548, 2005.

[17] ATIK Enver, MERIC Cevdet, KARLIK Bekir, “Determination of Hardness of AA 2024 Aluminum Alloy under Aging Conditions by Means of Artificial Neural Networks Method”, Journal of METALL, vol. 58, pp. 448-451, 2004.

[18]AYHAN Teoman, KARLIK Bekir, TANDIROGLU Ahmet, “Flow Geometry Optimization of Channels with Baffels Using Neural Networks and Second-Low of Thermodynamics”, Computational Mechanics, vol. 33, no: 2, pp.139-143, 2004.

[20]KARLIK Bekir, TOKHI Osman, ALCI Musa, “A Fuzzy Clustering Neural Network Architecture for Multi-Function Upper-Limb Prosthesis”, IEEE Trans. on Biomedical Engineering, vol. 50, no: 11, pp.1255-1261, 2003.

[21] KARLIK Bekir, AYDIN Serkan, “An Improved Approach to the Solution of Inverse Kinematics Problem for Robot Manipulator”, Engineering Applications of Artificial Intelligence, vol. 13, pp. 159-164, 2000.

[22] KARLIK Bekir, OZKAYA Erdogan, AYDIN Serkan, PAKDEMIRLI Mehmet, “Vibration of a Beam-Mass System Using Artificial Neural Networks”, Computer & Structures, vol. 69, pp.339-347, 1998.

Tamamlanmış Y.Lisans Tezleri

[1] Muhterem Çöl, “Servis Sistemlerine Yapay Sinir Ağları ile Yaklaşım ve Bir Uygulama”, Celal Bayar Üniversitesi, 1996.

[2] Hamdi Alper Özyiğit, “Taşıt Süspansiyon Sisteminin Yapay Sinir Ağları ile Kontrolü”, Celal Bayar Üniversitesi, 1996.

[3] Selahattin Kaya, “Yapay Sinir Ağları ile Ünite Planlaması ve Paylaşımı”, Sakarya Üniversitesi, 1997.

[4] Fatma Demirezen, “Yapay Sinir Ağları ile Retinada Hastalık Teşhisi”, Haliç Üniversitesi, 2008.

[5]Recep Kızılaslan, “Forecasting of Natural Gas Consumption in Istanbul Using Artificial Neural Networks”, Fatih Üniversitesi, 2008.

[6] Semra Kul, “Diagnosis of Lumbar Disc Hernia from Images Using Artificial Neural Network”, Fatih Üniversitesi, 2008.

[7] Elif Erdoğan, “Diagnosis of Brain Diseases Using Artificial Neural Network”, Fatih Üniversitesi, 2009.

[8] A. Vehbi Olgaç, “Software Development of Fuzzy Clustering Artificial Neural Networks”, Fatih Üniversites, 2009.

Tamamlanmış Doktora Tezleri

[1] Özbay, Y., “EKG Aritmilerini On-Line Tanımada Yeni Bir Yaklaşım” Selçuk Üniversitesi, 1998

[2] Rahime Ceylan, “Özellik Çıkarma Algoritmaları ve Yapay Sinir Ağları Kullanarak Bir Telekardiyoloji Sistem Tasarımı”, Selçuk Üniversitesi, 2009, (2. Danışman)

Prof. Dr. Mustafa Yıldız

Yayınlar:

[1] Seymen, P., Yildiz, M., Turkmen, MF., Titiz, MI. ve Seymen, HO., “Effects of cyclosporine-tacrolimus switching in posttransplant hyperlipidemia on HDL 2/3, lipoprotein A1/B and other lipid parameters”, Transplant Proc, 41 (10), 4181-4183 (2009).

[2] Ozkan M, Biteker M, Duran NE, Yildiz, M., “Images in cardiovascular medicine. Huge prosthetic mitral valve thrombosis in a pregnant woman”, Circulation, 120, e151-152 (2009).

[3] Kocabay, G., Yildiz, M. ve Ozkan, M., “A normally functioning caged-ball mitral prosthesis after 37 years without warfarin therapy”, J Heart Valve Disease, 18(6), 729 (2009).

[4] Yildiz, M. ve Akdemir, O., “Assessment the effects of physiological melatonin release on arterial distensibility and blood pressure”, Cardiol Young, 19, 198-203 (2009).

[5] Soy, M., Yıldız, M., Uyanık, MŞ., Karaca, N., Güfer, G ve Pişkin, S., “Susceptibility to atherosclerosis in patients with psoriasis and psoriatic arthritis as determined by carotid-femoral (aortic) pulse-wave velocity measurement”, Rev Esp Cardiol, 62, 96-99 (2009).

[6] Biteker, M., Ekşi Duran, N., Sungur Biteker, F., Ayyıldız Civan, H., Kaya, H., Gökdeniz, T., Yıldız, M. ve Ozkan, M., “Allergic myocardial infarction in childhood: Kounis syndrome,” Eur J Pediatr, Mar 11, PMID: 19277706 (2009).

[7] Yucel, O,, Sayan. A. ve Yildiz, M. “The factors associated with asymptomatic carriage of helicobacter pylori in children and their mothers living in three socio-economic settings”, Jpn J Infect Dis, 62:120-124 (2009).

[8] Yücel, O., Yildiz, M., Altinkaynak, S. ve Sayan, A., “P-wave dispersion and P-wave duration in children with stable asthma bronchiale”, Anadolu Kardiyol Derg, 9:118-122 (2009).

[9] Kocabay, G., Yildiz, M., Duran, NE ve Ozkan, M., “Acute inferior myocardial infarction due to cannabis smoking in a young man”, J Cardiovasc Med (Hagerstown), 10(9), 669-670 (2009).

[10] Ozkan, M., Kaya, H., Gökdeniz, T., Biteker, M., Ekşi Duran, N. ve Yildiz, M., “Perfect delineation of the localization and size of the paravalvular leak due to extensive suture loosening”, Anadolu Kardiyol Derg, 9(3), E6-7 (2009).

[11] Kocabay, G., Yildiz, M. ve Ozkan, M., “Acute myocardial infarction due to oral contraceptive”, Clin Appl Thromb Hemost, 15(3), 364-365 (2009).

[12] Yıldız, M., Pazarlı, P., Semiz, O., Kahyaoğlu, O., Şakar, İ ve Altınkaynak, S., “Assessment of P wave dispersion on 12-lead electrocardiography in students who exercise regularly”, PACE, 31, 580-583 (2008).

[13] Yıldız, M., Yıldız, SB. Soy, M ve Tutkan, H., “Impairment of arterial distensibility in premenopausal women with systemic lupus erythematosus”, Kardiol Pol, 66, 1194-1199 (2008).

[14] Yıldız, M., “Hypoxia is/is not the optimal means of reducing pulmonary blood flow in the preoperative single ventricle heart”, J Appl Physiol, 104(6), 1840 (2008).

[15] Yıldız, M., “Commentary on viewpoint: The human cutaneous circulation as a model of generalized microvascular function“, J Appl Physiol, 105(1):382 (2008).

[16] Yıldız, M., “Commentary on Viewpoint: Is left ventricular volume during diastasis the real equilibrium volume, and what is its relationship to diastolic suction? “, J Appl Physiol, 105(3):1018 (2008).

[17]Yildiz M., “Comments on Point:Counterpoint: Sympathetic activity does/does not influence cerebral blood flow”, J Appl Physiol, 105,1371 (2008).

[18] Yildiz, M., Biteker, M ve Ozkan, M., “Assessment of aortic stiffness and ventricular functions in familial Mediterranean fever”, Anadolu Kardiyol Derg, 8(5), 395 (2008).

[19] Yildiz, M., Duran, NE., Kocabay, G ve Ozkan, M., “An unreported cause of pacemaker dysfunction: Fracture of tines”, J Cardiovasc Electrophysiol, PMID: 18803568 (2008).

[20] Yıldız, M., Altun, A. ve Özbay, G., “Assessment of arterial distensibility in patients with cardiac syndrome X”, Angiology, 58, 458-462 (2007).

[21] Yıldız, M., Soy, M., Kürüm, T. ve Şahin Yıldız, M., “Arterial distensibility in Wegener’s granulomatosis: a carotid - femoral pulse wave velocity study”, The Anatolian Journal of Cardiology, 7, 281-285 (2007).

[22] Ozkan, M., Yıldız, M. ve Koker, I., “Images in Cardiology: Giant left main coronary artery aneurysm”, Can J Cardiol, 23, 743 (2007).

[23] Yıldız, M., Masatlıoglu, S., Seymen, P., Aytac, E.,Sahin, B. veSeymen, OH., “The carotid - femoral (aortic) pulse wave velocity as a marker of arterial stiffness in familial Mediterranean fever”, The Canadian J of Cardiology, 22, 1127-1131 (2006).

[24] Tatlı, E., Yıldız, M., Gül, Ç., Birsin, A., Karahasanoğlu, E., Özcelik, F. ve Özbay, G., “Effect of obesity on coronary collateral vessel development in patients with coronary artery disease,” Angiology, 56, 657-661 (2005).

[25] Kürüm, T., Yıldız, M., Soy, M., Özbay, G., Alimgil, L. ve Tüzün, B., “Arterial distensibility, as determined by carotid-femoral pulse wave velocity, in patients with Behçet’s Disease,” Clin Rheumatol, 24, 134-138 (2005).

[26] Yıldız, M., Soy, M., Kürüm, T. ve Özbay, G., “Increased pulse wave velocity and shortened pulse wave propagation time in young patients with rheumatoid arthritis,” Canadian J of Cardiology, 20, 1097-1100 (2004).

[27] Altun, A., Erdoğan, O. ve Yıldız, M., “Acute effect of DDD versus VVI pacing on arterial distensibility,” Cardiology, 102, 89-92 (2004).

[28] Durmus-Altun, G., Altun, A., Yıldız, M., Fırat, MF., Hacımahmutoğlu, S. ve Berkarda, S., “Irbesartan has a masking effect of dipyridamole stress - induced myocardial perfusion defects”, Nucl Med Commun, 25, 195-199 (2004).

[29] Akdemir, O., Dağdeviren, B., Yıldız, M., Gül, Ç., Sürücü, H. ve Özbay, G., “Specific tissue Doppler predictors of preserved systolic and diastolic left ventricular function after an acute anterior myocardial infarction”, Japn Heart J, 44, 347-355 (2003).

[30] Yıldız, M., Erdoğan, O., Aktoz, M., Gül Ç. ve Özbay, G., “Management of a patient with active rheumatoid arthritis and suspected tuberculosis causing effusive-constrictive pericarditis” International Journal of Cardiology, 89, 115-118 (2003).

[31] Akdemir, O., Yıldız, M., Sürücü, H., Dağdeviren, B., Erdoğan, O. ve Özbay, G., “Right ventricular function in patients with acute anterior myocardial infarction: tissue Doppler echocardiographic approach”, Acta Cardiol, 57, 399-405 (2002).

[32] Yıldız, M., Gül, Ç. ve Özbay, G., “Hyperosmolar hyperglycaemic nonketotic coma associated with acute myocardial infarction: report of three cases”, Acta Cardiol, 57, 271-274 (2002).

[33] Balci, H., Sipahi Demirkok, S., Yildiz, M., Metin, G., Hacıbekiroglu, M ve Simsek, G., “The evaluation of the relationship between the inflammatory markers and arterial distensibility in patients with sarcoidosis”, Trakya Üniversitesi Tıp Fakültesi Dergisi, (in press) (2010).