Najat Khan

471 total citations
15 papers, 167 citations indexed

About

Najat Khan is a scholar working on Epidemiology, Infectious Diseases and Oncology. According to data from OpenAlex, Najat Khan has authored 15 papers receiving a total of 167 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Epidemiology, 4 papers in Infectious Diseases and 4 papers in Oncology. Recurrent topics in Najat Khan's work include Radiomics and Machine Learning in Medical Imaging (3 papers), SARS-CoV-2 and COVID-19 Research (3 papers) and COVID-19 epidemiological studies (3 papers). Najat Khan is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (3 papers), SARS-CoV-2 and COVID-19 Research (3 papers) and COVID-19 epidemiological studies (3 papers). Najat Khan collaborates with scholars based in United States, Canada and Netherlands. Najat Khan's co-authors include Sebastian Schneeweiß, Tripthi Kamath, Venky Soundararajan, Michael Batech, AJ Venkatakrishnan, Arjun Puranik, Raymond A. Harvey, Carly Kabelac, Jeremy A. Rassen and Andrew R. Weckstein and has published in prestigious journals such as Journal of Clinical Oncology, SHILAP Revista de lepidopterología and Gastroenterology.

In The Last Decade

Najat Khan

14 papers receiving 161 citations

Peers

Countries citing papers authored by Najat Khan

Since Specialization

Citations

This map shows the geographic impact of Najat Khan'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 Najat Khan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Najat Khan more than expected).

Fields of papers citing papers by Najat Khan

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Najat Khan. 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 Najat Khan. The network helps show where Najat Khan may publish in the future.

Co-authorship network of co-authors of Najat Khan

This figure shows the co-authorship network connecting the top 25 collaborators of Najat Khan. A scholar is included among the top collaborators of Najat Khan 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 Najat Khan. Najat Khan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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15 of 15 papers shown

#	Work	Indexed citations
1	Combining Real‐World and Clinical Trial Data Through Privacy‐Preserving Record Linkage: Opportunities and Challenges—A Narrative Review 2025 ·Health Science Reports ·Michael Batech, Ann Madsen, Nicolle M. Gatto, (unknown), Deborah Ricci, Raymond A. Harvey, Najat Khan, (unknown)	0
2	Unbiased identification of risk factors for invasive Escherichia coli disease using machine learning 2024 ·BMC Infectious Diseases ·Erik Clarke, Christel Chehoud, Najat Khan, Bart Spiessens, Jan Poolman, Jeroen Geurtsen	3
3	Using Computer Vision to Improve Endoscopic Disease Quantification in Therapeutic Clinical Trials of Ulcerative Colitis 2023 ·Gastroenterology ·Ryan W. Stidham, (unknown), Shuyang Cheng, (unknown), (unknown), (unknown), Michael Rice, Shrinivas Bishu, Jan Wehkamp, (unknown), Najat Khan, Aleksandar Stojmirović, Louis R. Ghanem, Kayvan Najarian	30
4	Mo1736 PREDICTING REMISSION EARLY IN ULCERATIVE COLITIS CLINICAL TRIALS USING COMPUTER VISION ANALYSIS OF ENDOSCOPIC VIDEO 2023 ·Gastroenterology ·(unknown), (unknown), (unknown), (unknown), Shuyang Cheng, (unknown), (unknown), Michael Rice, Shrinivas Bishu, Jan Wehkamp, Najat Khan, Tommaso Mansi, Xiaoying Wu, (unknown), Aleksandar Stojmirović, Louis R. Ghanem, Kayvan Najarian	1
5	Creation of an ustekinumab external control arm for Crohn’s disease using electronic health records data: A pilot study 2023 ·PLoS ONE ·Vivek A. Rudrapatna, Yao‐Wen Cheng, (unknown), (unknown), Jonathan Shih, Yongmei Shi, (unknown), B. A. Rubin, Atul J. Butte, Uma Mahadevan, Nicholas Skomrock, Ngozi Erondu, Christel Chehoud, (unknown), (unknown), Mark Curran, Najat Khan, Christopher O’Brien, Natalie A. Terry, (unknown)	7
6	Data-Driven COVID-19 Vaccine Development for Janssen 2023 ·RePEc: Research Papers in Economics ·Dimitris Bertsimas, Michael Lingzhi Li, Xinggang Liu, Jennings Xu, Najat Khan	1
7	Digital histopathology-based multimodal artificial intelligence scores predict risk of progression in a randomized phase III trial in patients with nonmetastatic castration-resistant prostate cancer. 2023 ·Journal of Clinical Oncology ·Felix Y. Feng, Matthew R. Smith, Fred Saad, Pooya Mobadersany, Shaozhou K. Tian, (unknown), Joel Greshock, Najat Khan, Margaret K. Yu, Sharon McCarthy, Sabine Brookman‐May, Tamara R. Todorović, Rikiya Yamashita, Huei–Chung Huang, Timothy N. Showalter, Akinori Mitani, Andre Esteva, Eric J. Small	1
8	AI-enabled analysis of H&E-stained prostate cancer tissue images: Assessing risk for metastasis prior to apalutamide (APA) treatment of patients with non-metastatic castration-resistant prostate cancer (nmCRPC). 2023 ·Journal of Clinical Oncology ·Pooya Mobadersany, Shaozhou K. Tian, Stephen Yip, Joel Greshock, Najat Khan, Margaret K. Yu, Sharon McCarthy, Sabine Brookman‐May, Muhammad Hassan, (unknown), Wei Huang, Hirak S. Basu, George Wilding, Parag Jain, Rajat Roy, Eric J. Small, Fred Saad, Matthew R. Smith	2
9	Abstract 5053: Artificial intelligence (AI)-based multimodal framework predicts androgen-deprivation therapy (ADT) outcomes in non-metastatic castration resistant prostate cancer (nmCRPC) from SPARTAN 2022 ·Cancer Research ·Pooya Mobadersany, Justin Lucas, (unknown), Clemente Aguilar-Bonavides, Sharon McCarthy, Sabine Brookman‐May, Margaret K. Yu, (unknown), Natalie A. Hutnick, (unknown), Joel Greshock, Najat Khan, (unknown)	1
10	Durability of the Single-Dose Ad26.COV2.S Vaccine in the Prevention of COVID-19 Infections and Hospitalizations in the US Before and During the Delta Variant Surge 2022 ·JAMA Network Open ·Jennifer M. Polinski, Andrew R. Weckstein, Michael Batech, Carly Kabelac, Tripthi Kamath, Raymond A. Harvey, (unknown), Jeremy A. Rassen, Najat Khan, Sebastian Schneeweiß	37
11	Durability of Protection Post–Primary COVID-19 Vaccination in the United States 2022 ·Vaccines ·Amanda B. Zheutlin, Miles Q. Ott, Ran Sun, (unknown), Craig S. Meyer, Meagan Rubel, Jennifer Hayden, (unknown), Tripthi Kamath, Najat Khan, Sebastian Schneeweiß, Khaled Sarsour	12
12	An infodemiological framework for tracking the spread of SARS-CoV-2 using integrated public data 2022 ·Pattern Recognition Letters ·Zhimin Liu, Zuodong Jiang, (unknown), Kirti Snigdha, Jennings Xu, Xiaoying Wu, Najat Khan, (unknown)	2
13	796: COMPUTER VISION MEASUREMENT OF DISEASE SEVERITY DISTRIBUTION OUTPERFORMS TRADITIONAL ENDOSCOPIC SCORING FOR DETECTING THERAPEUTIC RESPONSE IN A CLINICAL TRIAL OF USTEKINUMAB FOR ULCERATIVE COLITIS 2022 ·Gastroenterology ·(unknown), Heming Yao, S. M. Reza Soroushmehr, Jonathan Gryak, (unknown), Michael Rice, Shrinivas Bishu, Louis R. Ghanem, Aleksandar Stojmirović, Jan Wehkamp, Xiaoying Wu, Najat Khan, Kayvan Najarian	1
14	Knowledge synthesis of 100 million biomedical documents augments the deep expression profiling of coronavirus receptors 2020 ·SHILAP Revista de lepidopterología ·AJ Venkatakrishnan, Arjun Puranik, Akash Anand, David Zemmour, Xiang Yao, Xiaoying Wu, (unknown), Dariusz K. Murakowski, (unknown), (unknown), Tyler Wagner, Enrique Garcia-Rivera, (unknown), Abhinav Garg, Rakesh Barve, (unknown), Najat Khan, Venky Soundararajan	46
15	Inference from longitudinal laboratory tests characterizes temporal evolution of COVID-19-associated coagulopathy (CAC) 2020 ·eLife ·Colin Pawlowski, (unknown), Arjun Puranik, (unknown), (unknown), AJ Venkatakrishnan, Rajiv K. Pruthi, Damon E. Houghton, John C. O’Horo, William G. Morice, Amy W. Williams, Gregory J. Gores, John Halamka, Andrew D. Badley, Elliot S. Barnathan, Hideo Makimura, Najat Khan, Venky Soundararajan	23

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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