Jacob Calvert

3.2k citations

57 papers · 2.1k indexed · 1 hit paper · h-index 23

Impact in

Health Informatics top 0.5%
- Artificial Intelligence in Healthcare and Education
Family Practice top 1%
- Clinical Reasoning and Diagnostic Skills

Papers in ⓘ

Epidemiology 29
- Sepsis Diagnosis and Treatment 24
Artificial Intelligence 16
- Machine Learning in Healthcare 15

Co-authors: Ritankar Das (38 shared papers)Jana Hoffman (32 shared papers)Uli K. Chettipally (10 shared papers)Melissa Jay (8 shared papers)Qingqing Mao (24 shared papers)Christopher Barton (7 shared papers)Lisa Shieh (3 shared papers)Thomas Desautels (6 shared papers)
Journals: Computers in Biology and Medicine (4 papers)Clinical Therapeutics (2 papers)Critical Care Medicine (2 papers)Nucleic Acids Research (2 papers)BMJ Open (2 papers)
Partner nations: United States United Kingdom Belgium

In The Last Decade

Jacob Calvert

54 papers receiving 2.0k citations

Hit Papers

align trajectories log scale

Prediction of Sepsis in the Intensive Care Unit With Minimal Electronic Health Record Data: A Machine Learning Approach 2016 · 339 citations

Peers

Countries citing papers authored by Jacob Calvert

Since Specialization

Citations

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

Fields of papers citing papers by Jacob Calvert

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Showing the 20 most-cited of 57 papers — load more, or switch the sort, to bring in the rest.

#	Work
1	Prediction of Sepsis in the Intensive Care Unit With Minimal Electronic Health Record Data: A Machine Learning Approach JMIR Medical Informatics ·Thomas Desautels, Jacob Calvert, Jana Hoffman, Melissa Jay, Yaniv Kerem, Lisa Shieh, David Shimabukuro, Uli K. Chettipally, Mitchell D. Feldman, Chris W. Barton, David J. Wales, Ritankar Das Hit paper breakdown →	2016	339
2	Multicentre validation of a sepsis prediction algorithm using only vital sign data in the emergency department, general ward and ICU BMJ Open ·Qingqing Mao, Melissa Jay, Jana Hoffman, Jacob Calvert, Christopher Barton, David Shimabukuro, Lisa Shieh, Uli K. Chettipally, Grant Fletcher, Yaniv Kerem, Yifan Zhou, Ritankar Das	2018	229
3	A computational approach to early sepsis detection Computers in Biology and Medicine ·Jacob Calvert, D A Price, Uli K. Chettipally, Christopher W. Barton, Mitchell D. Feldman, Jana Hoffman, Melissa Jay, Ritankar Das	2016	184
4	Evaluation of a machine learning algorithm for up to 48-hour advance prediction of sepsis using six vital signs Computers in Biology and Medicine ·Christopher Barton, Uli K. Chettipally, Yifan Zhou, Zirui Jiang, Anna Lynn-Palevsky, Sidney Le, Jacob Calvert, Ritankar Das	2019	115
5	Prediction of Acute Kidney Injury With a Machine Learning Algorithm Using Electronic Health Record Data Canadian Journal of Kidney Health and Disease ·Hamid Mohamadlou, Anna Lynn-Palevsky, Christopher Barton, Uli K. Chettipally, Lisa Shieh, Jacob Calvert, Nicholas Saber, Ritankar Das	2018	102
6	Prediction of respiratory decompensation in Covid-19 patients using machine learning: The READY trial Computers in Biology and Medicine ·Hoyt Burdick, Carson Lam, Samson Mataraso, Anna Siefkas, Gregory L. Braden, R. Phillip Dellinger, Andrea J. McCoy, Jean‐Louis Vincent, Abigail Green‐Saxena, Gina Barnes, Jana Hoffman, Jacob Calvert, Emily Pellegrini, Ritankar Das	2020	96
7	Pediatric Severe Sepsis Prediction Using Machine Learning Frontiers in Pediatrics ·Sidney Le, Jana Hoffman, Christopher Barton, Julie C. Fitzgerald, Angier Allen, Emily Pellegrini, Jacob Calvert, Ritankar Das	2019	83
8	Prediction of early unplanned intensive care unit readmission in a UK tertiary care hospital: a cross-sectional machine learning approach BMJ Open ·Thomas Desautels, Ritankar Das, Jacob Calvert, Monica Trivedi, Charlotte Summers, David J. Wales, Ari Ercole	2017	83
9	G-quadruplex formation in double strand DNA probed by NMM and CV fluorescence Nucleic Acids Research ·Alex Kreig, Jacob Calvert, Janet Sanoica, Emily Cullum, Ramreddy Tipanna, Sua Myong	2015	71
10	Telomeric Overhang Length Determines Structural Dynamics and Accessibility to Telomerase and ALT-Associated Proteins Structure ·Helen Hwang, Alex Kreig, Jacob Calvert, Justin D Lormand, Youngho Kwon, James M. Daley, Patrick Sung, Patricia L. Opresko, Sua Myong	2014	58
11	Supervised machine learning for the early prediction of acute respiratory distress syndrome (ARDS) Journal of Critical Care ·Sidney Le, Emily Pellegrini, Abigail Green‐Saxena, Charlotte Summers, Jana Hoffman, Jacob Calvert, Ritankar Das	2020	58
12	Using electronic health record collected clinical variables to predict medical intensive care unit mortality Annals of Medicine and Surgery ·Jacob Calvert, Qingqing Mao, Jana Hoffman, Melissa Jay, Thomas Desautels, Hamid Mohamadlou, Uli K. Chettipally, Ritankar Das	2016	50
13	A Digital Twins Machine Learning Model for Forecasting Disease Progression in Stroke Patients Applied Sciences ·Angier Allen, Anna Siefkas, Emily Pellegrini, Hoyt Burdick, Gina Barnes, Jacob Calvert, Qingqing Mao, Ritankar Das	2021	43
14	High-performance detection and early prediction of septic shock for alcohol-use disorder patients Annals of Medicine and Surgery ·Jacob Calvert, Thomas Desautels, Uli K. Chettipally, Christopher Barton, Jana Hoffman, Melissa Jay, Qingqing Mao, Hamid Mohamadlou, Ritankar Das	2016	42
15	Convolutional Neural Network Model for Intensive Care Unit Acute Kidney Injury Prediction Kidney International Reports ·Sidney Le, Angier Allen, Jacob Calvert, Paul M. Palevsky, Gregory L. Braden, Sharad Patel, Emily Pellegrini, Abigail Green‐Saxena, Jana Hoffman, Ritankar Das	2021	40
16	Using Transfer Learning for Improved Mortality Prediction in a Data-Scarce Hospital Setting PubMed ·Thomas Desautels, Jacob Calvert, Jana Hoffman, Qingqing Mao, Melissa Jay, Grant Fletcher, Chris W. Barton, Uli K. Chettipally, Yaniv Kerem, Ritankar Das	2017	40
17	A Racially Unbiased, Machine Learning Approach to Prediction of Mortality: Algorithm Development Study JMIR Public Health and Surveillance ·Angier Allen, Samson Mataraso, Anna Siefkas, Hoyt Burdick, Gregory L. Braden, R.P. Dellinger, Andrea J. McCoy, Emily Pellegrini, Jana Hoffman, Abigail Green‐Saxena, Gina Barnes, Jacob Calvert, Ritankar Das	2020	35
18	A Machine Learning Approach to Predict Deep Venous Thrombosis Among Hospitalized Patients Clinical and Applied Thrombosis/Hemostasis ·Logan Ryan, Samson Mataraso, Anna Siefkas, Emily Pellegrini, Gina Barnes, Abigail Green‐Saxena, Jana Hoffman, Jacob Calvert, Ritankar Das	2021	31
19	Predicting ventilator-associated pneumonia with machine learning Medicine ·Christine Giang, Jacob Calvert, Keyvan Rahmani, Gina Barnes, Anna Siefkas, Abigail Green‐Saxena, Jana Hoffman, Qingqing Mao, Ritankar Das	2021	26
20	Machine-Learning-Based Laboratory Developed Test for the Diagnosis of Sepsis in High-Risk Patients Diagnostics ·Jacob Calvert, Nicholas Saber, Jana Hoffman, Ritankar Das	2019	26

About Jacob Calvert

Jacob Calvert is a scholar working on Epidemiology, Artificial Intelligence, Surgery, Cardiology and Cardiovascular Medicine and Pulmonary and Respiratory Medicine, having authored 57 papers that have together received 2.1k indexed citations. Recurring topics across this work include Sepsis Diagnosis and Treatment (24 papers), Machine Learning in Healthcare (15 papers), COVID-19 diagnosis using AI (4 papers), Hemodynamic Monitoring and Therapy (4 papers), Venous Thromboembolism Diagnosis and Management (4 papers), Emergency and Acute Care Studies (4 papers), Respiratory Support and Mechanisms (4 papers) and Healthcare Technology and Patient Monitoring (3 papers). The work is most often cited by research in Health Informatics (217 citations), Family Practice (179 citations), Health Information Management (238 citations), Epidemiology (1.0k citations) and Artificial Intelligence (928 citations). Jacob Calvert has collaborated with scholars based in United States, United Kingdom and Belgium. Frequent co-authors include Ritankar Das, Jana Hoffman, Uli K. Chettipally, Melissa Jay, Qingqing Mao, Christopher Barton, Lisa Shieh, Thomas Desautels, Yaniv Kerem and Mitchell D. Feldman. Their work appears in journals such as Computers in Biology and Medicine, Clinical Therapeutics, Critical Care Medicine, Nucleic Acids Research 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.

Explore authors with similar magnitude of impact