Luke Geneslaw

3.2k total citations · 1 hit paper
4 papers, 1.5k citations indexed

About

Luke Geneslaw is a scholar working on Artificial Intelligence, Radiology, Nuclear Medicine and Imaging and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Luke Geneslaw has authored 4 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 3 papers in Artificial Intelligence, 2 papers in Radiology, Nuclear Medicine and Imaging and 1 paper in Pulmonary and Respiratory Medicine. Recurrent topics in Luke Geneslaw's work include AI in cancer detection (3 papers), Radiomics and Machine Learning in Medical Imaging (2 papers) and Digital Imaging in Medicine (1 paper). Luke Geneslaw is often cited by papers focused on AI in cancer detection (3 papers), Radiomics and Machine Learning in Medical Imaging (2 papers) and Digital Imaging in Medicine (1 paper). Luke Geneslaw collaborates with scholars based in United States. Luke Geneslaw's co-authors include Matthew G. Hanna, Thomas J. Fuchs, Victor E. Reuter, Edi Brogi, Gabriele Campanella, Vitor Werneck Krauss Silva, Klaus J. Busam, David S. Klimstra, Allen P. Miraflor and Dig Vijay Kumar Yarlagadda and has published in prestigious journals such as Nature Medicine, Journal of Clinical Oncology and Modern Pathology.

In The Last Decade

Luke Geneslaw

4 papers receiving 1.4k 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.

Clinical-grade computational pathology using weakly supervised deep learning on whole slide images

2019 1.4k citations Gabriele Campanella, Matthew G. Hanna et al. Nature Medicine profile →

Peers

Countries citing papers authored by Luke Geneslaw

Since Specialization

Citations

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

Fields of papers citing papers by Luke Geneslaw

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Luke Geneslaw

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

All Works

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4 of 4 papers shown

#	Work	Indexed citations
1	Digital pathology operations at a tertiary cancer center: Infrastructure requirements and operational cost 2023 ·Journal of Pathology Informatics ·Orly Ardon, Eric A. Klein, (unknown), Lorraine Corsale, Christine England, (unknown), Luke Geneslaw, John Philip, Peter Ntiamoah, (unknown), S. Joseph Sirintrapun, Oscar Lin, Kojo S.J. Elenitoba‐Johnson, Victor E. Reuter, Meera Hameed, Matthew G. Hanna	11
2	Multimodal integration of radiology, pathology, and genomics for prediction of response to PD-1 blockade in patients with non–small cell lung cancer. 2022 ·Journal of Clinical Oncology ·Jia Luo, R. Vanguri, (unknown), Jacklynn V. Egger, Christopher J. Fong, Natally Horvat, Andrew Pagano, José de Arimateia Batista Araújo-Filho, Luke Geneslaw, Hira Rizvi, Ramon E. Sosa, Kevin Boehm, Soo‐Ryum Yang, Katia Ventura, Travis Hollman, Michelle S. Ginsberg, Jianjiong Gao, Matthew D. Hellmann, Jennifer L. Sauter, Sohrab P. Shah	3
3	Multi-magnification-based machine learning as an ancillary tool for the pathologic assessment of shaved margins for breast carcinoma lumpectomy specimens 2021 ·Modern Pathology ·Timothy M. D’Alfonso, David Joon Ho, Matthew G. Hanna, Anne Grabenstetter, Dig Vijay Kumar Yarlagadda, Luke Geneslaw, Peter Ntiamoah, Thomas J. Fuchs, Lee K. Tan	16
4	Clinical-grade computational pathology using weakly supervised deep learning on whole slide images breakdown → 2019 ·Nature Medicine ·Gabriele Campanella, Matthew G. Hanna, Luke Geneslaw, Allen P. Miraflor, Vitor Werneck Krauss Silva, Klaus J. Busam, Edi Brogi, Victor E. Reuter, David S. Klimstra, Thomas J. Fuchs	1430

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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