Literature DB >> 35583620

Evaluation of Machine Learning Models for Clinical Prediction Problems.

L Nelson Sanchez-Pinto1, Tellen D Bennett2.   

Abstract

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Year:  2022        PMID： 35583620      PMCID： PMC9177058          DOI： 10.1097/PCC.0000000000002942

Source DB:  PubMed          Journal:  Pediatr Crit Care Med        ISSN： 1529-7535            Impact factor:   3.971


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  13 in total

1.  Clinician Perception of a Machine Learning-Based Early Warning System Designed to Predict Severe Sepsis and Septic Shock.

Authors:  Jennifer C Ginestra; Heather M Giannini; William D Schweickert; Laurie Meadows; Michael J Lynch; Kimberly Pavan; Corey J Chivers; Michael Draugelis; Patrick J Donnelly; Barry D Fuchs; Craig A Umscheid
Journal:  Crit Care Med       Date:  2019-11       Impact factor: 7.598

2.  Clinical Decision Support in the Era of Artificial Intelligence.

Authors:  Edward H Shortliffe; Martin J Sepúlveda
Journal:  JAMA       Date:  2018-12-04       Impact factor: 56.272

3.  Stop Explaining Black Box Machine Learning Models for High Stakes Decisions and Use Interpretable Models Instead.

Authors:  Cynthia Rudin
Journal:  Nat Mach Intell       Date:  2019-05-13

4.  Dynamic Mortality Risk Predictions for Children in ICUs: Development and Validation of Machine Learning Models.

Authors:  Eduardo A Trujillo Rivera; James M Chamberlain; Anita K Patel; Hiroki Morizono; Julia A Heneghan; Murray M Pollack
Journal:  Pediatr Crit Care Med       Date:  2022-05-05       Impact factor: 3.971

5.  A Machine Learning Algorithm to Predict Severe Sepsis and Septic Shock: Development, Implementation, and Impact on Clinical Practice.

Authors:  Heather M Giannini; Jennifer C Ginestra; Corey Chivers; Michael Draugelis; Asaf Hanish; William D Schweickert; Barry D Fuchs; Laurie Meadows; Michael Lynch; Patrick J Donnelly; Kimberly Pavan; Neil O Fishman; C William Hanson; Craig A Umscheid
Journal:  Crit Care Med       Date:  2019-11       Impact factor: 7.598

Review 6.  Interventions for improving the adoption of shared decision making by healthcare professionals.

Authors:  France Légaré; Dawn Stacey; Stéphane Turcotte; Marie-Joëlle Cossi; Jennifer Kryworuchko; Ian D Graham; Anne Lyddiatt; Mary C Politi; Richard Thomson; Glyn Elwyn; Norbert Donner-Banzhoff
Journal:  Cochrane Database Syst Rev       Date:  2014-09-15

7.  Early Prediction of Sepsis From Clinical Data: The PhysioNet/Computing in Cardiology Challenge 2019.

Authors:  Matthew A Reyna; Christopher S Josef; Russell Jeter; Supreeth P Shashikumar; M Brandon Westover; Shamim Nemati; Gari D Clifford; Ashish Sharma
Journal:  Crit Care Med       Date:  2020-02       Impact factor: 7.598

8.  Criticality: A New Concept of Severity of Illness for Hospitalized Children.

Authors:  Eduardo A Trujillo Rivera; Anita K Patel; James M Chamberlain; T Elizabeth Workman; Julia A Heneghan; Douglas Redd; Hiroki Morizono; Dongkyu Kim; James E Bost; Murray M Pollack
Journal:  Pediatr Crit Care Med       Date:  2021-01-01       Impact factor: 3.971

9.  Development and Reporting of Prediction Models: Guidance for Authors From Editors of Respiratory, Sleep, and Critical Care Journals.

Authors:  Daniel E Leisman; Michael O Harhay; David J Lederer; Michael Abramson; Alex A Adjei; Jan Bakker; Zuhair K Ballas; Esther Barreiro; Scott C Bell; Rinaldo Bellomo; Jonathan A Bernstein; Richard D Branson; Vito Brusasco; James D Chalmers; Sudhansu Chokroverty; Giuseppe Citerio; Nancy A Collop; Colin R Cooke; James D Crapo; Gavin Donaldson; Dominic A Fitzgerald; Emma Grainger; Lauren Hale; Felix J Herth; Patrick M Kochanek; Guy Marks; J Randall Moorman; David E Ost; Michael Schatz; Aziz Sheikh; Alan R Smyth; Iain Stewart; Paul W Stewart; Erik R Swenson; Ronald Szymusiak; Jean-Louis Teboul; Jean-Louis Vincent; Jadwiga A Wedzicha; David M Maslove
Journal:  Crit Care Med       Date:  2020-05       Impact factor: 7.598

10.  Comparing different supervised machine learning algorithms for disease prediction.

Authors:  Shahadat Uddin; Arif Khan; Md Ekramul Hossain; Mohammad Ali Moni
Journal:  BMC Med Inform Decis Mak       Date:  2019-12-21       Impact factor: 2.796
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