Jared Katzman

2.1k citations
9 papers · 1.1k · 1 hit paper · h-index 3

Impact in

Papers in

Jared Katzman

7 papers receiving 1.1k citations

Jared Katzman's Hit Papers

DeepSurv: personalized treatment recommender system using a Cox proportional hazards deep neural network 2018 · 1.0k citations
1.0k0+2+5Years since publication2505007501000

Peers

Jared Katzman
Comparison fields: 5 of 110
  • Health Informatics 21
  • Statistics and Probability 116
  • Radiology, Nuclear Medicine and Imaging 253
  • Artificial Intelligence 382
  • Health Information Management 33
Replace Jonathan Bates with:
Jonathan Bates United States
Uri Shaham United States
Michael F. Gensheimer United States
Safoora Yousefi United States
Nuria Ribelles Spain
Vanya Van Belle Belgium
Joseph A. Cruz Canada
Mohamed Amgad United States
R. Vanguri United States
Carlotta Masciocchi Italy
Jared Katzman relative to Jonathan Bates United States Jonathan Bates's profile →
Citations per field
00.5×1.5×
Jonathan Bates · 1×
Citations per year

Countries citing papers authored by Jared Katzman

Since Specialization
Citations

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

Fields of papers citing papers by Jared Katzman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Jared Katzman, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Jared Katzman Line = papers co-authored together Jared Katzman links everyone, so they are left out of the graph.

All Works

9 of 9 papers shown
#Work
1
DeepSurv: personalized treatment recommender system using a Cox proportional hazards deep neural network
Hit paper breakdown →
20181033
2 202319
3 202118
4 20252
5 20172
6 20251
7 20251
8 20250
9 20260

About Jared Katzman

Jared Katzman is a scholar working on Artificial Intelligence, Human-Computer Interaction, Information Systems, Safety Research and Food Science, having authored 9 papers that have together received 1.1k indexed citations. Recurring topics across this work include Innovative Human-Technology Interaction (3 papers), Food Waste Reduction and Sustainability (2 papers), Machine Learning in Healthcare (2 papers), Ethics and Social Impacts of AI (2 papers), ICT in Developing Communities (1 paper), Free Will and Agency (1 paper), Psychology of Moral and Emotional Judgment (1 paper) and Smart Cities and Technologies (1 paper). The work is most often cited by research in Health Informatics (21 citations), Statistics and Probability (116 citations), Radiology, Nuclear Medicine and Imaging (253 citations), Artificial Intelligence (382 citations) and Health Information Management (33 citations). Jared Katzman has collaborated with scholars based in United States, Australia and India. Frequent co-authors include Uri Shaham, Yuval Kluger, Tingting Jiang, Jonathan Bates, Alexander Cloninger, Su Lin Blodgett, Morgan Klaus Scheuerman, Angelina Wang, Hanna Wallach and Solon Barocas. Their work appears in journals such as BMC Medical Research Methodology, Figshare and Proceedings of the AAAI Conference on Artificial Intelligence.

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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