Literature DB >> 31707786

Machine learning probability calibration for high-risk clinical decision-making.

Micah Cearns1, Tim Hahn2, Scott Clark1, Bernhard T Baune1,3,4,5.   

Abstract

Year:  2019        PMID: 31707786     DOI: 10.1177/0004867419885448

Source DB:  PubMed          Journal:  Aust N Z J Psychiatry        ISSN: 0004-8674            Impact factor:   5.744


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  4 in total

1.  Commentary: Automated Machine Learning Model Development for Intracranial Aneurysm Treatment Outcome Prediction: A Feasibility Study.

Authors:  Markus Huber; Markus M Luedi; Lukas Andereggen
Journal:  Front Neurol       Date:  2022-06-10       Impact factor: 4.086

Review 2.  A Risk-Based IoT Decision-Making Framework Based on Literature Review with Human Activity Recognition Case Studies.

Authors:  Tazar Hussain; Chris Nugent; Adrian Moore; Jun Liu; Alfie Beard
Journal:  Sensors (Basel)       Date:  2021-06-30       Impact factor: 3.576

3.  External validation of Machine Learning models for COVID-19 detection based on Complete Blood Count.

Authors:  Andrea Campagner; Anna Carobene; Federico Cabitza
Journal:  Health Inf Sci Syst       Date:  2021-10-23

4.  Machine learning approaches for parsing comorbidity/heterogeneity in antisociality and substance use disorders: A primer.

Authors:  Matthew S Shane; William J Denomme
Journal:  Personal Neurosci       Date:  2021-11-15
  4 in total

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