Yaniv Kerem

1.4k citations
13 papers · 925 indexed · 1 hit paper · h-index 12

Yaniv Kerem

13 papers receiving 886 citations

Hit Papers

Prediction of Sepsis in the Intensive Care Unit With Mini...3392016202620192022100200300

Peers

Yaniv Kerem
Comparison fields: 5 of 92
  • Health Informatics 82
  • Family Practice 100
  • Health Information Management 92
  • Emergency Medicine 179
  • Epidemiology 436
Replace Melissa Jay with:
Melissa Jay United States
David Shimabukuro United States
Matthew D. Stanley United States
Thomas Desautels United States
Patrick Thoral Netherlands
Michael Draugelis United States
Andre L. Holder United States
Sidney Le United States
Asaf Hanish United States
Kyle A. Carey United States
Yaniv Kerem relative to Melissa Jay United States Melissa Jay's profile →
Citations per field
00.5×2.5×
Melissa Jay · 1×
Citations per year

Countries citing papers authored by Yaniv Kerem

Since Specialization
Citations

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

Fields of papers citing papers by Yaniv Kerem

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 25 scholars most cited alongside Yaniv Kerem, 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 Yaniv Kerem Line = papers co-authored together Yaniv Kerem links everyone, so they are left out of the graph.

All Works

13 of 13 papers shown
#Work
1 202213
2 202045
3 2018229
4 201740
5 201720
6
Prediction of Sepsis in the Intensive Care Unit With Minimal Electronic Health Record Data: A Machine Learning Approachbreakdown →
2016339
7 20152
8 201313
9 201388
10 201233
11 200732
12 200640
13 200631

About Yaniv Kerem

Yaniv Kerem is a scholar working on Emergency Medicine, Statistics and Probability and Rehabilitation, having authored 13 papers that have together received 925 indexed citations. Recurring topics across this work include Machine Learning in Healthcare (4 papers), Sepsis Diagnosis and Treatment (4 papers), Emergency and Acute Care Studies (2 papers), Lung Cancer Diagnosis and Treatment (2 papers), Statistical Methods in Epidemiology (2 papers), Hemodynamic Monitoring and Therapy (2 papers), Lung Cancer Treatments and Mutations (2 papers) and ECG Monitoring and Analysis (1 paper). The work is most often cited by research in Health Informatics (82 citations), Family Practice (100 citations) and Health Information Management (92 citations). Yaniv Kerem has collaborated with scholars based in United States and United Kingdom. Frequent co-authors include Melissa Jay, Ritankar Das, Jacob Calvert, Uli K. Chettipally, Jana Hoffman, David Shimabukuro, Lisa Shieh, Chris W. Barton, Thomas Desautels and Erik Kulstad. Their work appears in journals such as Journal of Thoracic and Cardiovascular Surgery, The Annals of Thoracic Surgery and BMJ Open.

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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