Mary Lin

604 total citations
11 papers, 400 citations indexed

About

Mary Lin is a scholar working on Radiology, Nuclear Medicine and Imaging, Genetics and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Mary Lin has authored 11 papers receiving a total of 400 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Radiology, Nuclear Medicine and Imaging, 3 papers in Genetics and 2 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Mary Lin's work include Radiomics and Machine Learning in Medical Imaging (3 papers), Inflammatory Bowel Disease (3 papers) and Prostate Cancer Diagnosis and Treatment (2 papers). Mary Lin is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (3 papers), Inflammatory Bowel Disease (3 papers) and Prostate Cancer Diagnosis and Treatment (2 papers). Mary Lin collaborates with scholars based in United States, Finland and Canada. Mary Lin's co-authors include Juha Partanen, Susan K. McConnell, Jean M. Hébert, Janet Rossant, K. S. Clifford Chao, Michael J. Zeléfsky, Xin Pei, Marisa Kollmeier, Sean M. McBride and Debra A. Goldman and has published in prestigious journals such as Journal of Clinical Oncology, Gastroenterology and Development.

In The Last Decade

Mary Lin

10 papers receiving 393 citations

Peers

Mary Lin

PRM

RADIA

GENET

Eun Kyung Paik South Korea

Laure Raymond France

Sylvia Ritter Germany

Slávka Lukacova Denmark

Minli Wang United States

Angel Moran United States

John H. Neal United States

Lina García‐Cañamaque Spain

Shunsuke Shinmei Japan

Vivek B. Beechar United States

Eun Kyung Paik South Korea

Mary Lin

139 ×0.9

PRM

129 ×1.0

78 ×0.7

RADIA

53 ×0.8

GENET

1 ×0.0

Citations per year, relative to Mary Lin Mary Lin (= 1×) peers Eun Kyung Paik

Countries citing papers authored by Mary Lin

Since Specialization

Citations

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

Fields of papers citing papers by Mary Lin

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mary Lin

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

All Works

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11 of 11 papers shown

Walker, Andrew, Geetika Singh, Mary Lin, et al.. (2023). Mo1754 MACHINE LEARNING-BASED PREDICTION OF GEBOES SCORE AND HISTOLOGIC IMPROVEMENT AND REMISSION THRESHOLDS IN ULCERATIVE COLITIS. Gastroenterology. 164(6). S–894.

Li, Jin, et al.. (2023). MACHINE LEARNING-BASED PREDICTION OF GEBOES SCORE AND HISTOLOGIC IMPROVEMENT AND REMISSION THRESHOLDS IN ULCERATIVE COLITIS. Gastroenterology. 164(4). S25–S26. 2 indexed citations

Lin, Mary, et al.. (2023). Artificial Intelligence Enables Quantitative Assessment of Ulcerative Colitis Histology. Modern Pathology. 36(6). 100124–100124. 28 indexed citations

Drage, Michael G., Yilan Wang, Mary Lin, et al.. (2023). QUANTITATIVE AND EXPLAINABLE ARTIFICIAL INTELLIGENCE (AI)-POWERED APPROACHES TO PREDICT ULCERATIVE COLITIS DISEASE ACTIVITY FROM HEMATOXYLIN AND EOSIN (H&E)-STAINED WHOLE SLIDE IMAGES (WSI). Inflammatory Bowel Diseases. 29(Supplement_1). S22–S23. 2 indexed citations

Shen, Ciyue, Mary Lin, Ilan Wapinski, et al.. (2022). Abstract 1922: Application of an interpretable graph neural network to predict gene expression signatures associated with tertiary lymphoid structures in histopathological images. Cancer Research. 82(12_Supplement). 1922–1922. 1 indexed citations

Buckley, Michael, Matthew J. Koch, Mary Lin, et al.. (2020). MSK eConsent: Digitalizing the informed consent process to improve participant engagement and understanding.. Journal of Clinical Oncology. 38(15_suppl). 2066–2066. 1 indexed citations

Zeléfsky, Michael J., Marisa Kollmeier, Sean M. McBride, et al.. (2019). Five-Year Outcomes of a Phase 1 Dose-Escalation Study Using Stereotactic Body Radiosurgery for Patients With Low-Risk and Intermediate-Risk Prostate Cancer. International Journal of Radiation Oncology*Biology*Physics. 104(1). 42–49. 89 indexed citations

Kollmeier, Marisa, Sean M. McBride, Amandeep Taggar, et al.. (2017). Salvage brachytherapy for recurrent prostate cancer after definitive radiation therapy: A comparison of low-dose-rate and high-dose-rate brachytherapy and the importance of prostate-specific antigen doubling time. Brachytherapy. 16(6). 1091–1098. 60 indexed citations

Zhang, Kevin, et al.. (2007). Dynamic Spectrum Access Enabled DoD Net-centric Spectrum Management. 1–7. 7 indexed citations

10.

Hébert, Jean M., Mary Lin, Juha Partanen, Janet Rossant, & Susan K. McConnell. (2003). FGF signaling through FGFR1 is required for olfactory bulb morphogenesis. Development. 130(6). 1101–1111. 174 indexed citations

11.

Chao, K. S. Clifford & Mary Lin. (2002). Lymphangiogram-assisted lymph node target delineation for patients with gynecologic malignancies. International Journal of Radiation Oncology*Biology*Physics. 54(4). 1147–1152. 36 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.

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