Literature DB >> 31714992

How to Read Articles That Use Machine Learning: Users' Guides to the Medical Literature.

Yun Liu1, Po-Hsuan Cameron Chen1, Jonathan Krause1, Lily Peng1.   

Abstract

In recent years, many new clinical diagnostic tools have been developed using complicated machine learning methods. Irrespective of how a diagnostic tool is derived, it must be evaluated using a 3-step process of deriving, validating, and establishing the clinical effectiveness of the tool. Machine learning-based tools should also be assessed for the type of machine learning model used and its appropriateness for the input data type and data set size. Machine learning models also generally have additional prespecified settings called hyperparameters, which must be tuned on a data set independent of the validation set. On the validation set, the outcome against which the model is evaluated is termed the reference standard. The rigor of the reference standard must be assessed, such as against a universally accepted gold standard or expert grading.

Mesh:

Year:  2019        PMID: 31714992     DOI: 10.1001/jama.2019.16489

Source DB:  PubMed          Journal:  JAMA        ISSN: 0098-7484            Impact factor:   56.272


  98 in total

Review 1.  Designing deep learning studies in cancer diagnostics.

Authors:  Andreas Kleppe; Ole-Johan Skrede; Sepp De Raedt; Knut Liestøl; David J Kerr; Håvard E Danielsen
Journal:  Nat Rev Cancer       Date:  2021-01-29       Impact factor: 60.716

2.  Autonomously Driven: Artificial Intelligence in Cardiothoracic Surgery.

Authors:  Brendan Jones; Benjamin Reed; Jw Awori Hayanga
Journal:  Ann Thorac Surg       Date:  2020-04-08       Impact factor: 4.330

3.  Geographic Distribution of US Cohorts Used to Train Deep Learning Algorithms.

Authors:  Amit Kaushal; Russ Altman; Curt Langlotz
Journal:  JAMA       Date:  2020-09-22       Impact factor: 56.272

Review 4.  Acute myeloid leukemia and artificial intelligence, algorithms and new scores.

Authors:  Nathan Radakovich; Matthew Cortese; Aziz Nazha
Journal:  Best Pract Res Clin Haematol       Date:  2020-06-07       Impact factor: 3.020

5.  Application of Artificial Intelligence Methods to Pharmacy Data for Cancer Surveillance and Epidemiology Research: A Systematic Review.

Authors:  Andrew E Grothen; Bethany Tennant; Catherine Wang; Andrea Torres; Bonny Bloodgood Sheppard; Glenn Abastillas; Marina Matatova; Jeremy L Warner; Donna R Rivera
Journal:  JCO Clin Cancer Inform       Date:  2020-11

Review 6.  Artificial Intelligence: A Primer for Breast Imaging Radiologists.

Authors:  Manisha Bahl
Journal:  J Breast Imaging       Date:  2020-06-19

7.  What is the foot strike pattern distribution in children and adolescents during running? A cross-sectional study.

Authors:  Bruno Augusto Giacomini; Tiê Parma Yamato; Alexandre Dias Lopes; Luiz Hespanhol
Journal:  Braz J Phys Ther       Date:  2020-10-11       Impact factor: 3.377

8.  Use of deep learning to develop continuous-risk models for adverse event prediction from electronic health records.

Authors:  Christopher Nielson; Martin G Seneviratne; Joseph R Ledsam; Shakir Mohamed; Nenad Tomašev; Natalie Harris; Sebastien Baur; Anne Mottram; Xavier Glorot; Jack W Rae; Michal Zielinski; Harry Askham; Andre Saraiva; Valerio Magliulo; Clemens Meyer; Suman Ravuri; Ivan Protsyuk; Alistair Connell; Cían O Hughes; Alan Karthikesalingam; Julien Cornebise; Hugh Montgomery; Geraint Rees; Chris Laing; Clifton R Baker; Thomas F Osborne; Ruth Reeves; Demis Hassabis; Dominic King; Mustafa Suleyman; Trevor Back
Journal:  Nat Protoc       Date:  2021-05-05       Impact factor: 13.491

9.  Rethinking PICO in the Machine Learning Era: ML-PICO.

Authors:  Xinran Liu; James Anstey; Ron Li; Chethan Sarabu; Reiri Sono; Atul J Butte
Journal:  Appl Clin Inform       Date:  2021-05-19       Impact factor: 2.342

10.  Machine Learning Models for Predicting Neonatal Mortality: A Systematic Review.

Authors:  Cheyenne Mangold; Sarah Zoretic; Keerthi Thallapureddy; Axel Moreira; Kevin Chorath; Alvaro Moreira
Journal:  Neonatology       Date:  2021-07-14       Impact factor: 4.035

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