Manisha Bahl

3.2k total citations
75 papers, 2.0k citations indexed

About

Manisha Bahl is a scholar working on Pulmonary and Respiratory Medicine, Radiology, Nuclear Medicine and Imaging and Artificial Intelligence. According to data from OpenAlex, Manisha Bahl has authored 75 papers receiving a total of 2.0k indexed citations (citations by other indexed papers that have themselves been cited), including 34 papers in Pulmonary and Respiratory Medicine, 33 papers in Radiology, Nuclear Medicine and Imaging and 28 papers in Artificial Intelligence. Recurrent topics in Manisha Bahl's work include AI in cancer detection (27 papers), Digital Radiography and Breast Imaging (25 papers) and Breast Cancer Treatment Studies (22 papers). Manisha Bahl is often cited by papers focused on AI in cancer detection (27 papers), Digital Radiography and Breast Imaging (25 papers) and Breast Cancer Treatment Studies (22 papers). Manisha Bahl collaborates with scholars based in United States, Belarus and South Korea. Manisha Bahl's co-authors include Constance D. Lehman, Jenny K. Hoang, Leslie R. Lamb, Julie Ann Sosa, Regina Barzilay, Jay A. Baker, Geunwon Kim, Paul H. Yi, Sujata V. Ghate and Hana L. Haver and has published in prestigious journals such as Nature reviews. Cancer, Cancer and Radiology.

In The Last Decade

Manisha Bahl

68 papers receiving 2.0k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Manisha Bahl United States 25 873 700 699 423 413 75 2.0k
Nicole A. Cipriani United States 23 250 0.3× 581 0.8× 168 0.2× 517 1.2× 663 1.6× 110 2.2k
Jung Hee Shin South Korea 38 1.2k 1.3× 426 0.6× 336 0.5× 584 1.4× 2.1k 5.1× 185 4.6k
Yuhao Dong China 20 1.3k 1.5× 390 0.6× 265 0.4× 234 0.6× 215 0.5× 50 2.0k
Simone Maurea Italy 29 1.2k 1.4× 383 0.5× 124 0.2× 337 0.8× 1.1k 2.7× 159 2.9k
Ok Hee Woo South Korea 23 801 0.9× 311 0.4× 254 0.4× 303 0.7× 158 0.4× 106 1.6k
Ji Soo Choi South Korea 26 1.4k 1.6× 351 0.5× 424 0.6× 299 0.7× 957 2.3× 106 2.9k
Musib Siddique United Kingdom 22 1.3k 1.5× 365 0.5× 119 0.2× 503 1.2× 236 0.6× 41 1.8k
Enrico Cassano Italy 31 1.0k 1.2× 463 0.7× 446 0.6× 499 1.2× 241 0.6× 149 2.5k
Bo Kyoung Seo South Korea 24 872 1.0× 255 0.4× 277 0.4× 170 0.4× 239 0.6× 100 1.6k

Countries citing papers authored by Manisha Bahl

Since Specialization
Citations

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

Fields of papers citing papers by Manisha Bahl

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Manisha Bahl

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

All Works

20 of 20 papers shown
1.
Chang, Jung Min, et al.. (2025). Clinical Application of Artificial Intelligence in Digital Breast Tomosynthesis. PubMed. 86(2). 205–205. 2 indexed citations
2.
Bahl, Manisha, et al.. (2025). AI to Reduce the Interval Cancer Rate of Screening Digital Breast Tomosynthesis. Radiology. 316(1). e241050–e241050.
3.
Haver, Hana L., Paul H. Yi, Jean Jeudy, & Manisha Bahl. (2024). Use of ChatGPT to Assign BI-RADS Assessment Categories to Breast Imaging Reports. American Journal of Roentgenology. 223(3). e2431093–e2431093. 5 indexed citations
4.
Haver, Hana L., Anuj Gupta, Emily B. Ambinder, et al.. (2024). Evaluating the Use of ChatGPT to Accurately Simplify Patient-centered Information about Breast Cancer Prevention and Screening. Radiology Imaging Cancer. 6(2). e230086–e230086. 27 indexed citations
5.
6.
Faupel‐Badger, Jessica M., Indu Kohaar, Manisha Bahl, et al.. (2024). Defining precancer: a grand challenge for the cancer community. Nature reviews. Cancer. 24(11). 792–809. 13 indexed citations
7.
Mercaldo, Sarah, et al.. (2023). Prediction of Surgical Upstaging Risk of Ductal Carcinoma In Situ Using Machine Learning Models. Journal of Breast Imaging. 5(6). 695–702. 4 indexed citations
8.
Haver, Hana L., Emily B. Ambinder, Manisha Bahl, et al.. (2023). Appropriateness of Breast Cancer Prevention and Screening Recommendations Provided by ChatGPT. Radiology. 307(4). 171 indexed citations
9.
Bahl, Manisha. (2023). A Step-by-Step Guide to Writing a Scientific Review Article. Journal of Breast Imaging. 5(4). 480–485. 1 indexed citations
10.
Bahl, Manisha & Bin Deng. (2023). Impact of pre-operative MRI on surgical management of screening digital breast tomosynthesis-detected invasive lobular carcinoma. Breast Cancer Research and Treatment. 204(2). 397–405.
11.
12.
Oseni, Tawakalitu O., et al.. (2020). Symptomatic ductal carcinoma in situ (DCIS): Upstaging risk and predictors. Clinical Imaging. 73. 101–107. 9 indexed citations
13.
Bahl, Manisha, Sarah Mercaldo, Pragya A. Dang, et al.. (2020). Breast Cancer Screening with Digital Breast Tomosynthesis: Are Initial Benefits Sustained?. Radiology. 295(3). 529–539. 27 indexed citations
14.
Lamb, Leslie R., Tawakalitu O. Oseni, Constance D. Lehman, & Manisha Bahl. (2020). Pre-operative MRI in patients with ductal carcinoma in situ: Is MRI useful for identifying additional disease?. European Journal of Radiology. 129. 109130–109130. 15 indexed citations
15.
Bahl, Manisha. (2020). Management of High-Risk Breast Lesions. Radiologic Clinics of North America. 59(1). 29–40. 20 indexed citations
16.
Lamb, Leslie R., Constance D. Lehman, Tawakalitu O. Oseni, & Manisha Bahl. (2019). Ductal Carcinoma In Situ (DCIS) at Breast MRI: Predictors of Upgrade to Invasive Carcinoma. Academic Radiology. 27(10). 1394–1399. 21 indexed citations
17.
Lamb, Leslie R., Manisha Bahl, Michele A. Gadd, & Constance D. Lehman. (2017). Flat Epithelial Atypia: Upgrade Rates and Risk-Stratification Approach to Support Informed Decision Making. Journal of the American College of Surgeons. 225(6). 696–701. 26 indexed citations
18.
Sepahdari, Ali R., et al.. (2015). Predictors of Multigland Disease in Primary Hyperparathyroidism: A Scoring System with 4D-CT Imaging and Biochemical Markers. American Journal of Neuroradiology. 36(5). 987–992. 39 indexed citations
19.
Bahl, Manisha, Jay A. Baker, Rachel A. Greenup, & Sujata V. Ghate. (2015). Evaluation of Pathologic Nipple Discharge: What is the Added Diagnostic Value of MRI?. Annals of Surgical Oncology. 22(S3). 435–441. 29 indexed citations
20.

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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