Maha Shady

1.8k total citations · 1 hit paper
10 papers, 522 citations indexed

About

Maha Shady is a scholar working on Artificial Intelligence, Radiology, Nuclear Medicine and Imaging and Surgery. According to data from OpenAlex, Maha Shady has authored 10 papers receiving a total of 522 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Artificial Intelligence, 4 papers in Radiology, Nuclear Medicine and Imaging and 3 papers in Surgery. Recurrent topics in Maha Shady's work include Radiomics and Machine Learning in Medical Imaging (4 papers), AI in cancer detection (4 papers) and Cancer Genomics and Diagnostics (3 papers). Maha Shady is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (4 papers), AI in cancer detection (4 papers) and Cancer Genomics and Diagnostics (3 papers). Maha Shady collaborates with scholars based in United States, Switzerland and Egypt. Maha Shady's co-authors include Tiffany Chen, Ming Y. Lu, Faisal Mahmood, Richard J. Chen, Drew F. K. Williamson, Jana Lipková, Mane Williams, Muhammad Shaban, Trevor Manz and Wei‐Hung Weng and has published in prestigious journals such as Nature Medicine, Journal of Clinical Oncology and Journal of the American College of Cardiology.

In The Last Decade

Maha Shady

10 papers receiving 518 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.

Pan-cancer integrative histology-genomic analysis via multimodal deep learning

2022 291 citations Richard J. Chen, Ming Y. Lu et al. Cancer Cell profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Maha Shady United States	5	354	270	98	97	91	10	522
Andrew Zhang United States	4	362 1.0×	265 1.0×	58 0.6×	88 0.9×	120 1.3×	6	619
Mane Williams United States	5	431 1.2×	338 1.3×	114 1.2×	127 1.3×	110 1.2×	6	707
Luca L. Weishaupt United States	3	288 0.8×	225 0.8×	50 0.5×	65 0.7×	85 0.9×	6	499
Ramón Viñas United Kingdom	6	263 0.7×	187 0.7×	133 1.4×	134 1.4×	46 0.5×	9	523
Benoît Schmauch France	8	370 1.0×	448 1.7×	134 1.4×	111 1.1×	69 0.8×	14	763
Pooya Mobadersany United States	5	432 1.2×	420 1.6×	125 1.3×	114 1.2×	94 1.0×	9	716
Jerome Cheng United States	14	305 0.9×	185 0.7×	58 0.6×	117 1.2×	75 0.8×	49	627
Amelie Echle Germany	9	362 1.0×	350 1.3×	115 1.2×	84 0.9×	67 0.7×	10	618
Chengkuan Chen United States	4	488 1.4×	372 1.4×	92 0.9×	113 1.2×	177 1.9×	5	807
Nikolas Stathonikos Netherlands	14	508 1.4×	328 1.2×	62 0.6×	78 0.8×	163 1.8×	32	687

Countries citing papers authored by Maha Shady

Since Specialization

Citations

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

Fields of papers citing papers by Maha Shady

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Maha Shady

This figure shows the co-authorship network connecting the top 25 collaborators of Maha Shady. A scholar is included among the top collaborators of Maha Shady 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 Maha Shady. Maha Shady 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:

10 of 10 papers shown

1.

Shady, Maha, et al.. (2024). The Impact of Mediterranean Diet on Patients with Hashimoto Thyroiditis. QJM. 117(Supplement_2). 2 indexed citations

2.

Lipková, Jana, Tiffany Chen, Ming Y. Lu, et al.. (2022). Deep learning-enabled assessment of cardiac allograft rejection from endomyocardial biopsies. Nature Medicine. 28(3). 575–582. 52 indexed citations

3.

Chen, Richard J., Ming Y. Lu, Drew F. K. Williamson, et al.. (2022). Pan-cancer integrative histology-genomic analysis via multimodal deep learning. Cancer Cell. 40(8). 865–878.e6. 291 indexed citations breakdown →

4.

Lu, Ming Y., Tiffany Chen, Drew F. K. Williamson, et al.. (2022). AI-BASED PATHOLOGY PREDICTS ORIGINS FOR CANCERS OF UNKNOWN PRIMARY. Journal of Pathology Informatics. 13. 100045–100045. 11 indexed citations

5.

Chen, Richard J., Ming Y. Lu, Drew F. K. Williamson, et al.. (2022). PAN-CANCER INTEGRATIVE HISTOLOGY-GENOMIC ANALYSIS VIA INTERPRETABLE MULTIMODAL DEEP LEARNING. Journal of Pathology Informatics. 13. 100057–100057. 5 indexed citations

6.

Lipková, Jana, Tiffany Chen, Ming Y. Lu, et al.. (2021). INTERNATIONAL EVALUATION OF WEAKLY-SUPERVISED AI-MODEL FOR CARDIAC ALLOGRAFT REJECTION SCREENING. Journal of the American College of Cardiology. 77(18). 520–520. 1 indexed citations

7.

Chen, Richard J., Ming Y. Lu, Maha Shady, et al.. (2021). Abstract PO-002: Pan-cancer integrative histology-genomic analysis via interpretable multimodal deep learning. Clinical Cancer Research. 27(5_Supplement). PO–2. 4 indexed citations

8.

Chen, Richard J., Ming Y. Lu, Wei‐Hung Weng, et al.. (2021). Multimodal Co-Attention Transformer for Survival Prediction in Gigapixel Whole Slide Images. 2021 IEEE/CVF International Conference on Computer Vision (ICCV). 3995–4005. 152 indexed citations

9.

Cheng, Michael L., Maha Shady, C Cipolla, et al.. (2017). Comparison of somatic mutation profiles from cell free DNA (cfDNA) versus tissue in metastatic urothelial carcinoma (mUC).. Journal of Clinical Oncology. 35(15_suppl). 4533–4533. 3 indexed citations

10.

Audenet, François, Mark T.A. Donoghue, Eugene J. Pietzak, et al.. (2017). Genomic comparison of matched primary and metastatic germ cell tumors (GCT).. Journal of Clinical Oncology. 35(15_suppl). 4556–4556. 1 indexed citations

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.

Explore authors with similar magnitude of impact