Most cited papers from Dascena (United States)

Dascena (United States)

What are the most cited papers from Dascena (United States)?

The most cited paper from Dascena (United States) is "Prediction of Sepsis in the Intensive Care Unit With Minimal Electronic Health Record Data: A Machine Learning Approach" (Thomas Desautels, Jacob S. Calvert, Jana L. Hoffman et al., 2016), with 542 citations. Next come "Effect of a machine learning-based severe sepsis prediction algorithm on patient survival and hospital length of stay: a randomised clinical trial" (404) and "Multicentre validation of a sepsis prediction algorithm using only vital sign data in the emergency department, general ward and ICU" (353).

Published TypeFieldAccessCitations

Showing 50 of 92 papers. Every paper is listed.

Most cited papers, sortable by citations and release date
#	Paper
1	Prediction of Sepsis in the Intensive Care Unit With Minimal Electronic Health Record Data: A Machine Learning Approach Thomas Desautels, Jacob S. Calvert, Jana L. Hoffman et al. · JMIR Medical Informatics Open access	30 Sep 2016	542
2	Effect of a machine learning-based severe sepsis prediction algorithm on patient survival and hospital length of stay: a randomised clinical trial David W. Shimabukuro, Christopher W. Barton, Mitchell D. Feldman et al. · BMJ Open Respiratory Research Open access	Nov 2017	404
3	Multicentre validation of a sepsis prediction algorithm using only vital sign data in the emergency department, general ward and ICU Qingqing Mao, Melissa Jay, Jana L. Hoffman et al. · BMJ Open Open access	2018	353
4	A computational approach to early sepsis detection Jacob S. Calvert, Daniel A. Price, Uli K. Chettipally et al. · Computers in Biology and Medicine Open access	11 May 2016	259
5	Evaluation of a machine learning algorithm for up to 48-hour advance prediction of sepsis using six vital signs Christopher Barton, Uli K. Chettipally, Yifan Zhou et al. · Computers in Biology and Medicine Open access	23 Apr 2019	181
6	Prediction of Acute Kidney Injury With a Machine Learning Algorithm Using Electronic Health Record Data Hamid Mohamadlou, Anna Lynn-Palevsky, Christopher Barton et al. · Canadian Journal of Kidney Health and Disease Open access	2018	164
7	Prediction of respiratory decompensation in Covid-19 patients using machine learning: The READY trial Hoyt Burdick, Carson Lam, Samson J. Mataraso et al. · Computers in Biology and Medicine Open access	6 Aug 2020	159
8	Reducing patient mortality, length of stay and readmissions through machine learning-based sepsis prediction in the emergency department, intensive care unit and hospital floor units Andrea J. McCoy, Ritankar Das · BMJ Open Quality Open access	Oct 2017	159
9	Prediction of early unplanned intensive care unit readmission in a UK tertiary care hospital: a cross-sectional machine learning approach Thomas Desautels, Ritankar Das, Jacob S. Calvert et al. · BMJ Open Open access	Sep 2017	133
10	Pediatric Severe Sepsis Prediction Using Machine Learning Sidney Le, Jana L. Hoffman, Christopher Barton et al. · Frontiers in Pediatrics Open access	11 Oct 2019	116
11	Supervised machine learning for the early prediction of acute respiratory distress syndrome (ARDS) Sidney Le, Emily Pellegrini, Abigail Green‐Saxena et al. · Journal of Critical Care Open access	24 Jul 2020	99
12	Assessing the effects of data drift on the performance of machine learning models used in clinical sepsis prediction Keyvan Rahmani, Rahul Thapa, Peiling Tsou et al. · International Journal of Medical Informatics	19 Nov 2022	98
13	Mortality prediction model for the triage of COVID-19, pneumonia, and mechanically ventilated ICU patients: A retrospective study Logan Ryan, Carson Lam, Samson J. Mataraso et al. · Annals of Medicine and Surgery Open access	3 Oct 2020	90
14	Effect of a sepsis prediction algorithm on patient mortality, length of stay and readmission: a prospective multicentre clinical outcomes evaluation of real-world patient data from US hospitals Hoyt Burdick, Eduardo Pino, Denise Gabel-Comeau et al. · BMJ Health & Care Informatics Open access	Apr 2020	83
15	Using electronic health record collected clinical variables to predict medical intensive care unit mortality Jacob S. Calvert, Qingqing Mao, Jana L. Hoffman et al. · Annals of Medicine and Surgery Open access	9 Sep 2016	83
16	Prediction of diabetic kidney disease with machine learning algorithms, upon the initial diagnosis of type 2 diabetes mellitus Angier O. Allen, Zohora Iqbal, Abigail Green‐Saxena et al. · BMJ Open Diabetes Research & Care Open access	2022	79
17	A Digital Twins Machine Learning Model for Forecasting Disease Progression in Stroke Patients Angier O. Allen, Anna C. Siefkas, Emily Pellegrini et al. · Applied Sciences Open access	16 Jun 2021	74
18	High-performance detection and early prediction of septic shock for alcohol-use disorder patients Jacob S. Calvert, Thomas Desautels, Uli K. Chettipally et al. · Annals of Medicine and Surgery Open access	10 May 2016	74
19	Convolutional Neural Network Model for Intensive Care Unit Acute Kidney Injury Prediction Sidney Le, Angier O. Allen, Jacob S. Calvert et al. · Kidney International Reports Open access	26 Feb 2021	70
20	Early prediction of severe acute pancreatitis using machine learning Rahul Thapa, Zohora Iqbal, Anurag Garikipati et al. · Pancreatology Open access	19 Oct 2021	60
21	Using Transfer Learning for Improved Mortality Prediction in a Data-Scarce Hospital Setting Thomas Desautels, Jacob S. Calvert, Jana L. Hoffman et al. · Biomedical Informatics Insights Open access	2017	57
22	A Machine Learning Approach to Predict Deep Venous Thrombosis Among Hospitalized Patients Logan Ryan, Samson J. Mataraso, Anna C. Siefkas et al. · Clinical and Applied Thrombosis/Hemostasis Open access	2021	56
23	A Racially Unbiased, Machine Learning Approach to Prediction of Mortality: Algorithm Development Study Angier O. Allen, Samson J. Mataraso, Anna C. Siefkas et al. · JMIR Public Health and Surveillance Open access	22 Oct 2020	56
24	Predicting Falls in Long-term Care Facilities: Machine Learning Study Rahul Thapa, Anurag Garikipati, Sepideh Shokouhi et al. · JMIR Aging Open access	7 Feb 2022	52
25	Predicting ventilator-associated pneumonia with machine learning Christine Giang, Jacob S. Calvert, Keyvan Rahmani et al. · Medicine Open access	11 Jun 2021	49
26	Early prediction of central line associated bloodstream infection using machine learning Keyvan Rahmani, Anurag Garikipati, Gina Barnes et al. · American Journal of Infection Control Open access	21 Aug 2021	44
27	Validation of a machine learning algorithm for early severe sepsis prediction: a retrospective study predicting severe sepsis up to 48 h in advance using a diverse dataset from 461 US hospitals Hoyt Burdick, Eduardo Pino, Denise Gabel-Comeau et al. · BMC Medical Informatics and Decision Making Open access	27 Oct 2020	44
28	Predicting pulmonary embolism among hospitalized patients with machine learning algorithms Logan Ryan, Jenish Maharjan, Samson J. Mataraso et al. · Pulmonary Circulation Open access	15 Dec 2021	41
29	A machine learning approach to identifying patients with pulmonary hypertension using real-world electronic health records Emily Kogan, Eva‐Maria Didden, Eileen Lee et al. · International Journal of Cardiology Open access	14 Dec 2022	34
30	Machine-Learning-Based Laboratory Developed Test for the Diagnosis of Sepsis in High-Risk Patients Jacob S. Calvert, Nicholas Saber, Jana L. Hoffman et al. · Diagnostics Open access	13 Feb 2019	34
31	Correlation of Population SARS-CoV-2 Cycle Threshold Values to Local Disease Dynamics: Exploratory Observational Study Chak Foon Tso, Anurag Garikipati, Abigail Green‐Saxena et al. · JMIR Public Health and Surveillance Open access	17 May 2021	31
32	A machine learning approach to predicting risk of myelodysplastic syndrome Ashwath Radhachandran, Anurag Garikipati, Zohora Iqbal et al. · Leukemia Research Open access	8 Jun 2021	29
33	Cost and mortality impact of an algorithm-driven sepsis prediction system Jacob S. Calvert, Jana L. Hoffman, Christopher Barton et al. · Journal of Medical Economics Open access	15 Mar 2017	29
34	COVID-19 and its effects on the digestive system Tingting Cao, Guqin Zhang, Emily Pellegrini et al. · World Journal of Gastroenterology Open access	25 Jun 2021	28
35	Machine Learning as a Precision-Medicine Approach to Prescribing COVID-19 Pharmacotherapy with Remdesivir or Corticosteroids Carson Lam, Anna C. Siefkas, Nicole Sitkin Zelin et al. · Clinical Therapeutics Open access	29 Mar 2021	25
36	Multitask Learning With Recurrent Neural Networks for Acute Respiratory Distress Syndrome Prediction Using Only Electronic Health Record Data: Model Development and Validation Study Carson Lam, Rahul Thapa, Jenish Maharjan et al. · JMIR Medical Informatics Open access	2 May 2022	24
37	Multicenter validation of a machine-learning algorithm for 48-h all-cause mortality prediction Hamid Mohamadlou, Saarang Panchavati, J.R. Calvert et al. · Health Informatics Journal Open access	30 Dec 2019	23
38	Machine learning early prediction of respiratory syncytial virus in pediatric hospitalized patients Chak Foon Tso, Carson Lam, Jacob S. Calvert et al. · Frontiers in Pediatrics Open access	4 Aug 2022	21
39	Semisupervised Deep Learning Techniques for Predicting Acute Respiratory Distress Syndrome From Time-Series Clinical Data: Model Development and Validation Study Carson Lam, Chak Foon Tso, Abigail Green‐Saxena et al. · JMIR Formative Research Open access	Aug 2021	20
40	Prediction of short-term mortality in acute heart failure patients using minimal electronic health record data Ashwath Radhachandran, Anurag Garikipati, Nicole Sitkin Zelin et al. · BioData Mining Open access	31 Mar 2021	20
41	Evaluating a sepsis prediction machine learning algorithm in the emergency department and intensive care unit: a before and after comparative study Hoyt Burdick, Eduardo Pino, Denise Gabel-Comeau et al. · bioRxiv (Cold Spring Harbor Laboratory) PreprintOpen access	28 Nov 2017	19
42	Massive external validation of a machine learning algorithm to predict pulmonary embolism in hospitalized patients Jieru Shen, Satish Casie Chetty, Sepideh Shokouhi et al. · Thrombosis Research Open access	2 Jun 2022	18
43	A computational approach to mortality prediction of alcohol use disorder inpatients Jacob S. Calvert, Qingqing Mao, Angela J. Rogers et al. · Computers in Biology and Medicine Open access	24 May 2016	17
44	Retrospective validation of a machine learning clinical decision support tool for myocardial infarction risk stratification Saarang Panchavati, Carson Lam, Nicole Sitkin Zelin et al. · Healthcare Technology Letters Open access	31 Aug 2021	16
45	Discharge recommendation based on a novel technique of homeostatic analysis Jacob S. Calvert, Daniel A. Price, Christopher W. Barton et al. · Journal of the American Medical Informatics Association Open access	28 Mar 2016	16
46	A comparative analysis of machine learning approaches to predict C. difficile infection in hospitalized patients Saarang Panchavati, Nicole Sitkin Zelin, Anurag Garikipati et al. · American Journal of Infection Control Open access	19 Jan 2022	15
47	Personalized stratification of hospitalization risk amidst COVID-19: A machine learning approach Carson Lam, Jacob S. Calvert, Anna C. Siefkas et al. · Health Policy and Technology Open access	4 Aug 2021	14
48	COVID-19 Evidence Accelerator: A parallel analysis to describe the use of Hydroxychloroquine with or without Azithromycin among hospitalized COVID-19 patients Mark D. Stewart et al. · PLoS ONE Open access	17 Mar 2021	13
49	Is Machine Learning a Better Way to Identify COVID-19 Patients Who Might Benefit from Hydroxychloroquine Treatment?—The IDENTIFY Trial Hoyt Burdick, Carson Lam, Samson J. Mataraso et al. · Journal of Clinical Medicine Open access	26 Nov 2020	12
50	Early prediction of prostate cancer risk in younger men using polygenic risk scores and electronic health records Amita Varma, Jenish Maharjan, Anurag Garikipati et al. · Cancer Medicine Open access	25 Jun 2022	11

Citations are OpenAlex's own counts, from its 2026-09-23 snapshot, so the ranking can differ from Google Scholar or Web of Science. A paper is listed for an institution when any of its authors gave it as an affiliation; retracted papers and papers whose citation count cannot be traced to citing works are left out, and a preprint and the article it became are shown once. Release dates are OpenAlex's: where a source gave only a month or a year, that is what is shown. How the lists are chosen.