Literature DB >> 28263936

Learning About Machine Learning: The Promise and Pitfalls of Big Data and the Electronic Health Record.

Rahul C Deo1, Brahmajee K Nallamothu2.   

Abstract

Entities:  

Keywords:  Editorials; heart failure; linear models; machine learning; medicine; risk factors

Mesh：

Year:  2016        PMID： 28263936      PMCID： PMC5832331          DOI： 10.1161/CIRCOUTCOMES.116.003308

Source DB:  PubMed          Journal:  Circ Cardiovasc Qual Outcomes        ISSN： 1941-7713


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  5 in total

1.  Early Detection of Heart Failure Using Electronic Health Records: Practical Implications for Time Before Diagnosis, Data Diversity, Data Quantity, and Data Density.

Authors:  Kenney Ng; Steven R Steinhubl; Christopher deFilippi; Sanjoy Dey; Walter F Stewart
Journal:  Circ Cardiovasc Qual Outcomes       Date:  2016-11-08

Review 2.  Population risk prediction models for incident heart failure: a systematic review.

Authors:  Justin B Echouffo-Tcheugui; Stephen J Greene; Lampros Papadimitriou; Faiez Zannad; Clyde W Yancy; Mihai Gheorghiade; Javed Butler
Journal:  Circ Heart Fail       Date:  2015-03-03       Impact factor: 8.790

3.  Multimarker approach for the prediction of heart failure incidence in the community.

Authors:  Raghava S Velagaleti; Philimon Gona; Martin G Larson; Thomas J Wang; Daniel Levy; Emelia J Benjamin; Jacob Selhub; Paul F Jacques; James B Meigs; Geoffrey H Tofler; Ramachandran S Vasan
Journal:  Circulation       Date:  2010-10-11       Impact factor: 29.690

4.  Predictors of incident heart failure in a large insured population: a one million person-year follow-up study.

Authors:  Abhinav Goyal; Catherine R Norton; Tracy N Thomas; Robert L Davis; Javed Butler; Varun Ashok; Liping Zhao; Viola Vaccarino; Peter W F Wilson
Journal:  Circ Heart Fail       Date:  2010-08-26       Impact factor: 8.790

Review 5.  Machine Learning in Medicine.

Authors:  Rahul C Deo
Journal:  Circulation       Date:  2015-11-17       Impact factor: 29.690
  5 in total
  10 in total

Review 1.  Comparative Effectiveness Research in Pediatric Respiratory Disease: Promise and Pitfalls.

Authors:  Kathleen J Ramos; Ranjani Somayaji; David P Nichols; Christopher H Goss
Journal:  Paediatr Drugs       Date:  2018-02       Impact factor: 3.022

2.  The Promise of Big Data: Opportunities and Challenges.

Authors:  Harlan M Krumholz
Journal:  Circ Cardiovasc Qual Outcomes       Date:  2016-11-08

Review 3.  Machine Learning to Predict, Detect, and Intervene Older Adults Vulnerable for Adverse Drug Events in the Emergency Department.

Authors:  Kei Ouchi; Charlotta Lindvall; Peter R Chai; Edward W Boyer
Journal:  J Med Toxicol       Date:  2018-06-01

4.  Machine learning versus traditional risk stratification methods in acute coronary syndrome: a pooled randomized clinical trial analysis.

Authors:  William J Gibson; Tarek Nafee; Ryan Travis; Megan Yee; Mathieu Kerneis; Magnus Ohman; C Michael Gibson
Journal:  J Thromb Thrombolysis       Date:  2020-01       Impact factor: 2.300

5.  Clinical Value of Predicting Individual Treatment Effects for Intensive Blood Pressure Therapy.

Authors:  Tony Duan; Pranav Rajpurkar; Dillon Laird; Andrew Y Ng; Sanjay Basu
Journal:  Circ Cardiovasc Qual Outcomes       Date:  2019-03

6.  The Validity of Machine Learning Procedures in Orthodontics: What Is Still Missing?

Authors:  Pietro Auconi; Tommaso Gili; Silvia Capuani; Matteo Saccucci; Guido Caldarelli; Antonella Polimeni; Gabriele Di Carlo
Journal:  J Pers Med       Date:  2022-06-11

7.  Causal Inference Network of Genes Related with Bone Metastasis of Breast Cancer and Osteoblasts Using Causal Bayesian Networks.

Authors:  Sung Bae Park; Chun Kee Chung; Efrain Gonzalez; Changwon Yoo
Journal:  J Bone Metab       Date:  2018-11-30

8.  The roles of predictors in cardiovascular risk models - a question of modeling culture?

Authors:  Christine Wallisch; Asan Agibetov; Daniela Dunkler; Maria Haller; Matthias Samwald; Georg Dorffner; Georg Heinze
Journal:  BMC Med Res Methodol       Date:  2021-12-18       Impact factor: 4.615

Review 9.  The role of artificial intelligence in paediatric neuroradiology.

Authors:  Catherine Pringle; John-Paul Kilday; Ian Kamaly-Asl; Stavros Michael Stivaros
Journal:  Pediatr Radiol       Date:  2022-03-26

10.  Development and Validation of a Simplified Prehospital Triage Model Using Neural Network to Predict Mortality in Trauma Patients: The Ability to Follow Commands, Age, Pulse Rate, Systolic Blood Pressure and Peripheral Oxygen Saturation (CAPSO) Model.

Authors:  Yun Li; Lu Wang; Yuyan Liu; Yan Zhao; Yong Fan; Mengmeng Yang; Rui Yuan; Feihu Zhou; Zhengbo Zhang; Hongjun Kang
Journal:  Front Med (Lausanne)       Date:  2021-12-10
  10 in total

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