Literature DB >> 30394238

Introduction to Machine Learning in Digital Healthcare Epidemiology.

Jan A Roth1, Manuel Battegay1, Fabrice Juchler1, Julia E Vogt2, Andreas F Widmer1.   

Abstract

To exploit the full potential of big routine data in healthcare and to efficiently communicate and collaborate with information technology specialists and data analysts, healthcare epidemiologists should have some knowledge of large-scale analysis techniques, particularly about machine learning. This review focuses on the broad area of machine learning and its first applications in the emerging field of digital healthcare epidemiology.

Mesh：

Year:  2018        PMID： 30394238     DOI： 10.1017/ice.2018.265

Source DB:  PubMed          Journal:  Infect Control Hosp Epidemiol        ISSN： 0899-823X            Impact factor:   3.254


  8 in total

1.  Predicting probability of perirectal colonization with carbapenem-resistant Enterobacteriaceae (CRE) and other carbapenem-resistant organisms (CROs) at hospital unit admission.

Authors:  Katherine E Goodman; Patricia J Simner; Eili Y Klein; Abida Q Kazmi; Avinash Gadala; Matthew F Toerper; Scott Levin; Pranita D Tamma; Clare Rock; Sara E Cosgrove; Lisa L Maragakis; Aaron M Milstone
Journal:  Infect Control Hosp Epidemiol       Date:  2019-03-27       Impact factor: 3.254

2.  Machine Learning in Infectious Disease for Risk Factor Identification and Hypothesis Generation: Proof of Concept Using Invasive Candidiasis.

Authors:  Lisa M Mayer; Jeffrey R Strich; Sameer S Kadri; Michail S Lionakis; Nicholas G Evans; D Rebecca Prevots; Emily E Ricotta
Journal:  Open Forum Infect Dis       Date:  2022-08-03       Impact factor: 4.423

3.  Real-world Antimicrobial Stewardship Experience in a Large Academic Medical Center: Using Statistical and Machine Learning Approaches to Identify Intervention "Hotspots" in an Antibiotic Audit and Feedback Program.

Authors:  Katherine E Goodman; Emily L Heil; Kimberly C Claeys; Mary Banoub; Jacqueline T Bork
Journal:  Open Forum Infect Dis       Date:  2022-06-10       Impact factor: 4.423

Review 4.  Machine Learning Techniques for Hypoglycemia Prediction: Trends and Challenges.

Authors:  Omer Mujahid; Ivan Contreras; Josep Vehi
Journal:  Sensors (Basel)       Date:  2021-01-14       Impact factor: 3.576

5.  Developing practical clinical tools for predicting neonatal mortality at a neonatal intensive care unit in Tanzania.

Authors:  Dory Kovacs; Delfina R Msanga; Stephen E Mshana; Muhammad Bilal; Katarina Oravcova; Louise Matthews
Journal:  BMC Pediatr       Date:  2021-12-01       Impact factor: 2.125

6.  Osteoporosis Pre-Screening Using Ensemble Machine Learning in Postmenopausal Korean Women.

Authors:  Youngihn Kwon; Juyeon Lee; Joo Hee Park; Yoo Mee Kim; Se Hwa Kim; Young Jun Won; Hyung-Yong Kim
Journal:  Healthcare (Basel)       Date:  2022-06-14

7.  Concept and Proof of the Lifelog Bigdata Platform for Digital Healthcare and Precision Medicine on the Cloud.

Authors:  Kyu Hee Lee; Erdenebayar Urtnasan; Sangwon Hwang; Hee Young Lee; Jung Hun Lee; Sang Baek Koh; Hyun Youk
Journal:  Yonsei Med J       Date:  2022-01       Impact factor: 2.759

8.  Cohort-Derived Machine Learning Models for Individual Prediction of Chronic Kidney Disease in People Living With Human Immunodeficiency Virus: A Prospective Multicenter Cohort Study.

Authors:  Jan A Roth; Gorjan Radevski; Catia Marzolini; Andri Rauch; Huldrych F Günthard; Roger D Kouyos; Christoph A Fux; Alexandra U Scherrer; Alexandra Calmy; Matthias Cavassini; Christian R Kahlert; Enos Bernasconi; Jasmina Bogojeska; Manuel Battegay
Journal:  J Infect Dis       Date:  2021-10-13       Impact factor: 7.759
  8 in total

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