The chart shows the distribution of publications by all Research.com ranked scientists in the field of Computer Science in 2026. The highlighted bar marks where Nahum Kiryati sits on this spectrum.
This scientist: 150 publications — 27th percentile
27% of scientists in this discipline score the same or lower.
The last bar groups every scientist with 991 publications or more.
The chart shows the D-index (discipline H-index) distribution of Computer Science scientists ranked by Research.com in 2026. The highlighted bar marks where Nahum Kiryati sits on this spectrum.
This scientist: 45 D-Index — 51st percentile
51% of scientists in this discipline score the same or lower.
The last bar groups every scientist with 131 D-Index or more.
Nahum Kiryati is affiliated with Tel Aviv University in Israel and has contributed extensively to research at the intersection of medicine and computer science. Their work focuses primarily on medical imaging, advanced image processing, and applications of artificial intelligence in healthcare.
The main fields of study associated with their research are Medicine and Computer Science. More specifically, key subfields include Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition, Artificial Intelligence, Health Informatics, and Surgery.
Key topics covered in Nahum Kiryati's publications reflect a focus on radiomics and machine learning in medical imaging, AI in cancer detection, advanced image processing techniques, advanced MRI techniques and applications, advanced neural network applications, image and signal denoising methods, and COVID-19 diagnosis using AI.
Frequent coauthors collaborating with Nahum Kiryati include:
Among notable publication venues, Nahum Kiryati has appeared multiple times in the Journal of Imaging, arXiv (Cornell University), and Lecture Notes in Computer Science. Other venues include PLoS ONE and the International Journal of Computer Assisted Radiology and Surgery.
The following are selected recent papers by Nahum Kiryati and close collaborators:
Nahum Kiryati's work frequently engages with machine learning methods and neural networks to improve diagnostic accuracy and enhance imaging techniques, supporting applications such as cancer detection and accelerated MRI processes. The integration of AI in medical imaging is a recurrent theme throughout their body of research.
N. Kiryati;Y. Eldar;A. M. Bruckstein
D. Caspi;N. Kiryati;J. Shamir
Ron Kimmel;Doron Shaked;Nahum Kiryati;Alfred M. Bruckstein
Yoav Y. Schechner;Nahum Kiryati
G. Zigelman;R. Kimmel;N. Kiryati
H. Greenspan;G. Oz;N. Kiryati;S. Peled
Tali Basha;Yael Moses;Nahum Kiryati
Yoav Y. Schechner;Nahum Kiryati;Ronen Basri
Eli Horn;Nahum Kiryati
Yoav Y. Schechner;Joseph Shamir;Nahum Kiryati
Ron Kimmel;Nahum Kiryati;Alfred M. Bruckstein
Leah Bar;Nahum Kiryati;Nir Sochen
Nahum Kiryati;Yossi Gofman
Y.Y. Schechner;J. Shamir;N. Kiryati
L. Bar;A. Brook;N. Sochen;N. Kiryati
Leah Bar;Nir Sochen;Nahum Kiryati
D. Shaked;O. Yaron;N. Kiryati
Nahum Kiryati;Tamar Riklin-Raviv;Yan Ivanchenko;Shay Rochel
L. Bar;N. Sochen;N. Kiryati
Nahum Kiryati;Gabor Székely
Y. Gofman;N. Kiryati
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