Faisal Mahmood

7.8k total citations · 10 hit papers
78 papers, 3.5k citations indexed

About

Faisal Mahmood is a scholar working on Artificial Intelligence, Radiology, Nuclear Medicine and Imaging and Computer Vision and Pattern Recognition. According to data from OpenAlex, Faisal Mahmood has authored 78 papers receiving a total of 3.5k indexed citations (citations by other indexed papers that have themselves been cited), including 37 papers in Artificial Intelligence, 27 papers in Radiology, Nuclear Medicine and Imaging and 14 papers in Computer Vision and Pattern Recognition. Recurrent topics in Faisal Mahmood's work include AI in cancer detection (32 papers), Radiomics and Machine Learning in Medical Imaging (20 papers) and Artificial Intelligence in Healthcare and Education (10 papers). Faisal Mahmood is often cited by papers focused on AI in cancer detection (32 papers), Radiomics and Machine Learning in Medical Imaging (20 papers) and Artificial Intelligence in Healthcare and Education (10 papers). Faisal Mahmood collaborates with scholars based in United States, Pakistan and Japan. Faisal Mahmood's co-authors include Richard J. Chen, Ming Y. Lu, Drew F. K. Williamson, Tiffany Chen, Jana Lipková, Chengkuan Chen, Bowen Chen, Muhammad Shaban, Anurag Vaidya and Guillaume Jaume and has published in prestigious journals such as Nature, Cell and Proceedings of the National Academy of Sciences.

In The Last Decade

Faisal Mahmood

71 papers receiving 3.4k citations

Hit Papers

5 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.

Synthetic data in machine learning for medicine and healthcare

2021 414 citations Richard J. Chen, Ming Y. Lu et al. Nature Biomedical Engineering profile →
Artificial intelligence for multimodal data integration in oncology

2022 333 citations Jana Lipková, Richard J. Chen et al. Cancer Cell profile →
Towards a general-purpose foundation model for computational pathology

2024 331 citations Richard J. Chen, Ming Y. Lu et al. Nature Medicine profile →
Pan-cancer integrative histology-genomic analysis via multimodal deep learning

2022 291 citations Richard J. Chen, Ming Y. Lu et al. Cancer Cell profile →
Scaling Vision Transformers to Gigapixel Images via Hierarchical Self-Supervised Learning

2022 261 citations Richard J. Chen, Chengkuan Chen et al. profile →
Algorithmic fairness in artificial intelligence for medicine and healthcare

2023 253 citations Richard J. Chen, Drew F. K. Williamson et al. Nature Biomedical Engineering profile →
A visual-language foundation model for computational pathology

2024 228 citations Ming Y. Lu, Bowen Chen et al. Nature Medicine profile →
A multimodal generative AI copilot for human pathology

2024 156 citations Ming Y. Lu, Bowen Chen et al. profile →
Artificial intelligence for digital and computational pathology

2023 103 citations Andrew H. Song, Guillaume Jaume et al. profile →
A guide to artificial intelligence for cancer researchers

2024 89 citations Faisal Mahmood, Jakob Nikolas Kather et al. profile →

Peers

Countries citing papers authored by Faisal Mahmood

Since Specialization

Citations

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

Fields of papers citing papers by Faisal Mahmood

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Faisal Mahmood

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

#	Work	Indexed citations
1	Synthesis of bioactive Mercury-Picrate Analogue: Synthesis, Characterization, and Biomedical Applications 2025 ·(unknown), M. Atif, (unknown), (unknown), (unknown), Faisal Mahmood, Mazhar Mehmood, M. Afzal	0
2	Generative Artificial Intelligence in Anatomic Pathology 2025 ·Archives of Pathology & Laboratory Medicine ·(unknown), Ehsan Ullah, Andrey Bychkov, Andrew H. Song, Eric Walk, (unknown), Ghulam Rasool, Vikram Singh, Faisal Mahmood, Marilyn M. Bui, Anil V. Parwani	7
3	A benchmarking crisis in biomedical machine learning 2025 ·Nature Medicine ·Faisal Mahmood	9
4	A nano-bioengineered cobalt oxide biostimulant mediated regulation of physiological, biochemical, and antioxidant mechanisms in Zea mays 2025 ·Scientific Reports ·Yun Wang, Tuba Tariq, Faisal Mahmood, Mansour Ghorbanpour, Ghazala Mustafa, Murtaza Hasan	1
5	cAMP/PKA signaling regulates TDP-43 aggregation and mislocalization 2024 ·Proceedings of the National Academy of Sciences ·Diana M. Ho, Muhammad Shaban, Faisal Mahmood, (unknown), (unknown), David Van Vactor, Spyros Artavanis‐Tsakonas	6
6	Analysis of 3D pathology samples using weakly supervised AI 2024 ·Cell ·Andrew H. Song, Mane Williams, Drew F. K. Williamson, (unknown), Guillaume Jaume, Gan Gao, Andrew Zhang, Bowen Chen, Alexander S. Baras, Robert Serafin, Richard Colling, Michelle R. Downes, Xavier Farré, Peter A. Humphrey, Clare Verrill, Lawrence D. True, Anil V. Parwani, Jonathan Liu, Faisal Mahmood	27
7	Artificial intelligence 2024 ·Cancer Cell ·Moritz Gerstung, David Liu, Marzyeh Ghassemi, James Zou, Diego Chowell, Jonas Teuwen, Faisal Mahmood, Jakob Nikolas Kather	6
8	MAPS: pathologist-level cell type annotation from tissue images through machine learning 2024 ·Nature Communications ·Muhammad Shaban, Yunhao Bai, (unknown), (unknown), Jason Yeung, Yao Yu Yeo, Vignesh Shanmugam, Han Chen, Bokai Zhu, Jason L. Weirather, Garry P. Nolan, Margaret A. Shipp, Scott J. Rodig, Sizun Jiang, Faisal Mahmood	16
9	Triage of 3D pathology data via 2.5D multiple-instance learning to guide pathologist assessments 2024 ·Gan Gao, Andrew H. Song, (unknown), (unknown), (unknown), (unknown), Kevin W. Bishop, Lawrence D. True, Faisal Mahmood, Jonathan Liu	2
10	Artificial Intelligence–Triaged 3-Dimensional Pathology to Improve Detection of Esophageal Neoplasia While Reducing Pathologist Workloads 2023 ·Modern Pathology ·Lindsey A. Barner, Gan Gao, Deepti Reddi, (unknown), Wynn Burke, Faisal Mahmood, William M. Grady, Jonathan Liu	7
11	Bioinspired Cobalt Oxide Nanoball Synthesis, Characterization, and Their Potential as Metal Stress Absorbants 2023 ·ACS Omega ·Faisal Mahmood, (unknown), Murtaza Hasan, Ayesha Zafar, Tuba Tariq, Muhammad Imran Abdullah, (unknown), Muhammad Jamil, Shahbaz Gul Hassan, Xue Huang, Hafiz Umer Javed, Xugang Shu	18
12	Multiple-instance learning of somatic mutations for the classification of tumour type and the prediction of microsatellite status 2023 ·Nature Biomedical Engineering ·Jordan Anaya, John-William Sidhom, Faisal Mahmood, Alexander S. Baras	6
13	Fridolin: participatory design and evaluation of a nutrition chatbot for older adults 2023 ·i-com ·(unknown), Faisal Mahmood, (unknown), (unknown), Thomas Ludwig, Rainer Wieching	8
14	A unifying force for the realization of medical AI 2022 ·npj Digital Medicine ·Jochen K. Lennerz, Ursula Green, Drew F. K. Williamson, Faisal Mahmood	12
15	Artificial intelligence for multimodal data integration in oncology breakdown → 2022 ·Cancer Cell ·Jana Lipková, Richard J. Chen, Bowen Chen, Ming Y. Lu, Matteo Barbieri, (unknown), Anurag Vaidya, Chengkuan Chen, Luoting Zhuang, Drew F. K. Williamson, Muhammad Shaban, Tiffany Chen, Faisal Mahmood	333
16	Fast and scalable search of whole-slide images via self-supervised deep learning 2022 ·Nature Biomedical Engineering ·Chengkuan Chen, Ming Y. Lu, Drew F. K. Williamson, Tiffany Chen, (unknown), Faisal Mahmood	55
17	EndoSLAM dataset and an unsupervised monocular visual odometry and depth estimation approach for endoscopic videos 2021 ·Medical Image Analysis ·Kutsev Bengisu Ozyoruk, (unknown), Taylor L. Bobrow, (unknown), (unknown), Yasin Almalıoğlu, Faisal Mahmood, (unknown), (unknown), (unknown), (unknown), Hélder Araújo, Henrique Alexandrino, Nicholas J. Durr, Hunter B. Gilbert, Mehmet Turan	118
18	Synthetic data in machine learning for medicine and healthcare breakdown → 2021 ·Nature Biomedical Engineering ·Richard J. Chen, Ming Y. Lu, Tiffany Chen, Drew F. K. Williamson, Faisal Mahmood	414
19	Semi-supervised breast cancer histology classification using deep multiple instance learning and contrast predictive coding (Conference Presentation) 2020 ·Ming Y. Lu, Richard J. Chen, Faisal Mahmood	23
20	Learning to Navigate Endoscopic Capsule Robots 2019 ·IEEE Robotics and Automation Letters ·Mehmet Turan, Yasin Almalıoğlu, Hunter B. Gilbert, Faisal Mahmood, Nicholas J. Durr, Hélder Araújo, (unknown), Anurag Ajay, Metin Sitti	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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