Narges Razavian

5.2k total citations · 2 hit papers
39 papers, 2.7k citations indexed

About

Narges Razavian is a scholar working on Artificial Intelligence, Radiology, Nuclear Medicine and Imaging and Molecular Biology. According to data from OpenAlex, Narges Razavian has authored 39 papers receiving a total of 2.7k indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Artificial Intelligence, 9 papers in Radiology, Nuclear Medicine and Imaging and 6 papers in Molecular Biology. Recurrent topics in Narges Razavian's work include AI in cancer detection (8 papers), Radiomics and Machine Learning in Medical Imaging (7 papers) and Machine Learning in Healthcare (4 papers). Narges Razavian is often cited by papers focused on AI in cancer detection (8 papers), Radiomics and Machine Learning in Medical Imaging (7 papers) and Machine Learning in Healthcare (4 papers). Narges Razavian collaborates with scholars based in United States, Greece and Switzerland. Narges Razavian's co-authors include David Fenyö, Theodore Sakellaropoulos, Matija Snuderl, Aristotelis Tsirigos, Nicolas Coudray, Navneet Narula, Paolo Ocampo, André L. Moreira, David Sontag and Mark Olfson and has published in prestigious journals such as Nature Medicine, PLoS ONE and Cancer Research.

In The Last Decade

Narges Razavian

34 papers receiving 2.6k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Classification and mutation prediction from non–small cell lung cancer histopathology images using deep learning

2018 1.7k citations Nicolas Coudray, Paolo Ocampo et al. Nature Medicine profile →
Association of Psychiatric Disorders With Mortality Among Patients With COVID-19

2021 239 citations Narges Razavian et al. profile →

Peers

Countries citing papers authored by Narges Razavian

Since Specialization

Citations

This map shows the geographic impact of Narges Razavian's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Narges Razavian with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Narges Razavian more than expected).

Fields of papers citing papers by Narges Razavian

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Narges Razavian. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Narges Razavian. The network helps show where Narges Razavian may publish in the future.

Co-authorship network of co-authors of Narges Razavian

This figure shows the co-authorship network connecting the top 25 collaborators of Narges Razavian. A scholar is included among the top collaborators of Narges Razavian based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Narges Razavian. Narges Razavian is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

#	Work	Indexed citations
1	Catalyzing Health AI by Fixing Payment Systems 2025 ·NEJM AI ·Narges Razavian, (unknown), (unknown), Olivier Elemento, Pranav Rajpurkar, Suchi Saria, Nigam H. Shah, Eric J. Topol	0
2	Identification of patients at risk for pancreatic cancer in a 3-year timeframe based on machine learning algorithms 2025 ·Scientific Reports ·Weicheng Zhu, Long Chen, Yindalon Aphinyanaphongs, Fay Kastrinos, Diane M. Simeone, Mark Pochapin, (unknown), Narges Razavian, Tamas A. Gonda	0
3	Predicting Alzheimer’s Diseases and Related Dementias in 3‐year timeframe with AI Foundation Model on Electronic Health Records 2024 ·Alzheimer s & Dementia ·(unknown), (unknown), (unknown), (unknown), (unknown), (unknown), Xinyue Ma, Sumit Chopra, John A. Dodson, Abraham A. Brody, Arjun V. Masurkar, Narges Razavian	1
4	Generalizable deep learning model for early Alzheimer’s disease detection from structural MRIs 2022 ·Scientific Reports ·Sheng Liu, Arjun V. Masurkar, Henry Rusinek, Jingyun Chen, Ben Zhang, Weicheng Zhu, Carlos Fernandez‐Granda, Narges Razavian	90
5	Artificial intelligence and deep learning to map immune cell types in inflamed human tissue 2022 ·Journal of Immunological Methods ·(unknown), Yi Li, (unknown), Ding Yuan, Amrutesh S. Puranik, Cynthia A. Loomis, Narges Razavian, Timothy B. Niewold	4
6	Deep multi-task learning and random forest for series classification by pulse sequence type and orientation 2022 ·Neuroradiology ·(unknown), Matthew Lee, Narges Razavian, Yvonne W. Lui	2
7	Predicting endometrial cancer subtypes and molecular features from histopathology images using multi-resolution deep learning models 2021 ·Cell Reports Medicine ·Runyu Hong, (unknown), Deborah F. DeLair, Narges Razavian, David Fenyö	80
8	Deep Learning and Pathomics Analyses Reveal Cell Nuclei as Important Features for Mutation Prediction of BRAF-Mutated Melanomas 2021 ·Journal of Investigative Dermatology ·Randie H. Kim, Sofia Nomikou, Nicolas Coudray, George Jour, (unknown), Runyu Hong, (unknown), Theodore Sakellaropoulos, Douglas M. Donnelly, Una Moran, (unknown), Jeffrey S. Weber, Narges Razavian, Iannis Aifantis, David Fenyö, Matija Snuderl, Richard L. Shapiro, Russell S. Berman, Iman Osman, Aristotelis Tsirigos	27
9	Intermediate Layers Matter in Momentum Contrastive Self Supervised Learning 2021 ·arXiv (Cornell University) ·Aakash Kaku, (unknown), Narges Razavian	1
10	Early-Learning Regularization Prevents Memorization of Noisy Labels 2020 ·Neural Information Processing Systems ·Sheng Liu, Jonathan Niles‐Weed, Narges Razavian, Carlos Fernandez‐Granda	13
11	BERT-XML: Large Scale Automated ICD Coding Using BERT Pretraining 2020 ·(unknown), (unknown), Narges Razavian	38
12	Artificial intelligence and cancer 2020 ·Nature Cancer ·Olga G. Troyanskaya, Zlatko Trajanoski, Anne E. Carpenter, Sebastian Thrun, Narges Razavian, Nuria Oliver	30
13	Augmented reality microscopes for cancer histopathology 2019 ·Nature Medicine ·Narges Razavian	12
14	Predicting childhood obesity using electronic health records and publicly available data 2019 ·PLoS ONE ·Rob Hammond, Rodoniki Athanasiadou, Silvia Curado, Yindalon Aphinyanaphongs, Courtney Abrams, Mary Jo Messito, Rachel S. Gross, Michelle Katzow, Melanie Jay, Narges Razavian, Brian Elbel	57
15	P1.09-32 Classification and Mutation Prediction from Non-Small Cell Lung Cancer Histopathology Images Using Deep Learning 2018 ·Journal of Thoracic Oncology ·Paolo Ocampo, André L. Moreira, Nicolas Coudray, Theodore Sakellaropoulos, Navneet Narula, Matija Snuderl, David Fenyö, Narges Razavian, Aristotelis Tsirigos	13
16	Classification and mutation prediction from non–small cell lung cancer histopathology images using deep learning breakdown → 2018 ·Nature Medicine ·Nicolas Coudray, Paolo Ocampo, Theodore Sakellaropoulos, Navneet Narula, Matija Snuderl, David Fenyö, André L. Moreira, Narges Razavian, Aristotelis Tsirigos	1738
17	Visual Exploration of Temporal Data in Electronic Medical Records. 2015 ·AMIA ·Josua Krause, Narges Razavian, Enrico Bertini, David Sontag	1
18	Population-Level Prediction of Type 2 Diabetes From Claims Data and Analysis of Risk Factors 2015 ·Big Data ·Narges Razavian, Saul Blecker, Ann Marie Schmidt, Aaron Smith–McLallen, S. Nigam, David Sontag	137
19	Learning generative models of molecular dynamics 2012 ·BMC Genomics ·Narges Razavian, Hetunandan Kamisetty, Christopher J. Langmead	7
20	Fixed Length Word Suffix for Factored Statistical Machine Translation 2010 ·Meeting of the Association for Computational Linguistics ·Narges Razavian, Stephan Vogel	7

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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