Jeffrey L. Fine

1.4k total citations
46 papers, 1.0k citations indexed

About

Jeffrey L. Fine is a scholar working on Artificial Intelligence, Surgery and Molecular Biology. According to data from OpenAlex, Jeffrey L. Fine has authored 46 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Artificial Intelligence, 10 papers in Surgery and 10 papers in Molecular Biology. Recurrent topics in Jeffrey L. Fine's work include AI in cancer detection (13 papers), Breast Cancer Treatment Studies (9 papers) and Optical Coherence Tomography Applications (6 papers). Jeffrey L. Fine is often cited by papers focused on AI in cancer detection (13 papers), Breast Cancer Treatment Studies (9 papers) and Optical Coherence Tomography Applications (6 papers). Jeffrey L. Fine collaborates with scholars based in United States, Australia and Belgium. Jeffrey L. Fine's co-authors include Anil V. Parwani, Liron Pantanowitz, Jonhan Ho, Michael Montalto, Huda Akil, Stanley J. Watson, Howard B. Gutstein, Steffi Oesterreich, Nancy E. Davidson and D. Lansing Taylor and has published in prestigious journals such as Journal of Clinical Investigation, Cancer Research and Oncogene.

In The Last Decade

Jeffrey L. Fine

44 papers receiving 1.0k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jeffrey L. Fine United States 19 337 318 175 169 165 46 1.0k
Phedias Diamandis Canada 22 571 1.7× 362 1.1× 210 1.2× 81 0.5× 320 1.9× 60 1.6k
Ugljesa Djuric Canada 19 746 2.2× 242 0.8× 88 0.5× 28 0.2× 222 1.3× 24 1.5k
Scott Lipnick United States 15 567 1.7× 86 0.3× 58 0.3× 72 0.4× 171 1.0× 20 1.3k
Laleh Montaser‐Kouhsari Iran 18 218 0.6× 135 0.4× 129 0.7× 65 0.4× 83 0.5× 34 849
Ken Asada Japan 22 521 1.5× 222 0.7× 76 0.4× 33 0.2× 335 2.0× 44 1.3k
G. Clarke Canada 15 164 0.5× 126 0.4× 53 0.3× 63 0.4× 154 0.9× 26 601
Nicholas Knoblauch United States 11 489 1.5× 134 0.4× 170 1.0× 38 0.2× 85 0.5× 15 1.1k
Kei Kato Japan 17 116 0.3× 208 0.7× 250 1.4× 76 0.4× 200 1.2× 38 999
Lucy Yates United Kingdom 12 622 1.8× 232 0.7× 533 3.0× 26 0.2× 217 1.3× 16 1.7k
Jennifer Eschbacher United States 27 277 0.8× 61 0.2× 150 0.9× 215 1.3× 950 5.8× 80 2.8k

Countries citing papers authored by Jeffrey L. Fine

Since Specialization
Citations

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

Fields of papers citing papers by Jeffrey L. Fine

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jeffrey L. Fine. 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 Jeffrey L. Fine. The network helps show where Jeffrey L. Fine may publish in the future.

Co-authorship network of co-authors of Jeffrey L. Fine

This figure shows the co-authorship network connecting the top 25 collaborators of Jeffrey L. Fine. A scholar is included among the top collaborators of Jeffrey L. Fine 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 Jeffrey L. Fine. Jeffrey L. Fine 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.
Dai, Wenli, Jeffrey L. Fine, Samaneh Motanagh, et al.. (2025). Not All HER2-Positive Breast Cancers Are the Same: Intratumoral Heterogeneity, Low-Level HER2 Amplification, and Their Impact on Neoadjuvant Therapy Response. Modern Pathology. 38(7). 100785–100785. 3 indexed citations
2.
3.
Zhang, Wei, Jeffrey L. Fine, Ting Zhang, et al.. (2024). Characteristics and utility of high-resolution optical coherence microscopy images of endocervical canal lesions. American Journal of Clinical Pathology. 162(4). 392–400. 1 indexed citations
4.
Clark, Beth Z., T. Rinda Soong, Esther Elishaev, et al.. (2024). A comprehensive analysis of SOX17 expression by immunohistochemistry in human epithelial tumors, with an emphasis on gynecologic tumors. American Journal of Clinical Pathology. 163(1). 143–152. 2 indexed citations
5.
Clark, Beth Z., Jeffrey L. Fine, Jing Yu, et al.. (2024). Upgrade Rates of Variant Lobular Carcinoma In Situ Compared to Classic Lobular Carcinoma In Situ Diagnosed in Core Needle Biopsies: A 10-Year Single Institution Retrospective Study. Modern Pathology. 37(4). 100462–100462. 1 indexed citations
6.
Elishaev, Esther, T. Rinda Soong, Mirka W. Jones, et al.. (2023). Utility of TRPS1 immunohistochemistry in confirming breast carcinoma: Emphasis on staining in triple-negative breast cancers and gynecologic tumors. American Journal of Clinical Pathology. 160(4). 425–434. 8 indexed citations
7.
Wilson, Machelle, et al.. (2022). Effectiveness of an Opioid Stewardship Guideline in Renal Transplant Recipients Post-Discharge. Journal of Pain & Palliative Care Pharmacotherapy. 37(1). 44–51. 2 indexed citations
8.
Elishaev, Esther, T. Rinda Soong, Mirka W. Jones, et al.. (2022). The Utility of SOX10 Immunohistochemical Staining in Breast Pathology. American Journal of Clinical Pathology. 158(5). 616–625. 5 indexed citations
9.
Fine, Jeffrey L., et al.. (2021). Educational Case: High-Grade Serous Carcinoma of the Ovary. Academic Pathology. 8. 2466131731–2466131731. 1 indexed citations
10.
Tosun, Akif Burak, et al.. (2017). Spatial Statistics for Segmenting Histological Structures in H&E Stained Tissue Images. IEEE Transactions on Medical Imaging. 36(7). 1522–1532. 20 indexed citations
11.
Farahani, Navid, et al.. (2017). Pathologists' Computer-Assisted Diagnosis: A Mock-up of a Prototype Information System to Facilitate Automation of Pathology Sign-out. Archives of Pathology & Laboratory Medicine. 141(10). 1413–1420. 5 indexed citations
12.
Farahani, Navid, Ishtiaque Ahmed, Sara E. Monaco, et al.. (2016). Exploring virtual reality technology and the Oculus Rift for the examination of digital pathology slides. Journal of Pathology Informatics. 7(1). 22–22. 52 indexed citations
13.
Gyanchandani, Rekha, Yousef Al‐Kofahi, Andrew M. Stern, et al.. (2016). Pointwise mutual information quantifies intratumor heterogeneity in tissue sections labeled with multiple fluorescent biomarkers. Journal of Pathology Informatics. 7(1). 47–47. 16 indexed citations
14.
15.
Fine, Jeffrey L.. (2014). 21st century workflow: A proposal. Journal of Pathology Informatics. 5(1). 44–44. 19 indexed citations
16.
Filkins, Robert J., et al.. (2013). Relationship between magnification and resolution in digital pathology systems. Journal of Pathology Informatics. 4(1). 21–21. 53 indexed citations
17.
Pantanowitz, Liron, et al.. (2013). Tumor-to-tumor metastasis (TTM) of breast carcinoma within a solitary renal angiomyolipoma: A case report. Pathology - Research and Practice. 209(9). 605–608. 11 indexed citations
18.
Fine, Jeffrey L.. (2011). Comment on “Modified full-field optical coherence tomography: A novel tool for rapid histology of fresh tissues”. Journal of Pathology Informatics. 2(1). 29–29. 2 indexed citations
19.
Fine, Jeffrey L., Larry Kagemann, Gadi Wollstein, Hiroshi Ishikawa, & Joel S. Schuman. (2010). Direct Scanning of Pathology Specimens Using Spectral Domain Optical Coherence Tomography: A Pilot Study. Ophthalmic surgery, lasers & imaging retina. 41(S1). S58–64. 16 indexed citations
20.
Horbinski, Craig, Jeffrey L. Fine, Rafael Medina‐Flores, Yukako Yagi, & Clayton A. Wiley. (2007). Telepathology for Intraoperative Neuropathologic Consultations at an Academic Medical Center: A 5-Year Report. Journal of Neuropathology & Experimental Neurology. 66(8). 750–759. 42 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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