Machine Learning in Risk Prediction-Reference-Cited by-同舟云学术

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Machine Learning in Risk Prediction

Published:2020-05 Issue:5 Volume:75 Page:1165-1166
ISSN:0194-911X
Container-title:Hypertension
language:en
Short-container-title:Hypertension

Author:

Sundström Johan¹²,Schön Thomas B.³

Affiliation:

1. From the Clinical Epidemiology Unit, Department of Medical Sciences (J.S.), Uppsala University, Sweden

2. George Institute for Global Health, University of New South Wales, Sydney, Australia (J.S.).

3. Division of Systems and Control, Department of Information Technology (T.B.S.), Uppsala University, Sweden

Publisher

Ovid Technologies (Wolters Kluwer Health)

Subject

Internal Medicine

Reference12 articles.

1. Probabilistic machine learning and artificial intelligence

2. Machine learning: Trends, perspectives, and prospects

3. Modern modelling techniques are data hungry: a simulation study for predicting dichotomous endpoints

4. Assessment of Claims of Improved Prediction Beyond the Framingham Risk Score

5. Use and Misuse of the Receiver Operating Characteristic Curve in Risk Prediction

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1. Factors influencing clinician and patient interaction with machine learning-based risk prediction models: a systematic review;The Lancet Digital Health;2024-02

2. Predictive modeling for the development of diabetes mellitus using key factors in various machine learning approaches;Diabetes Epidemiology and Management;2024-01

3. PowerAI-CVD – the first Chinese-specific, validated artificial intelligence-poweredin-silicopredictive model for cardiovascular disease;2023-10-09

4. Prediction of diabetic kidney disease risk using machine learning models: A population-based cohort study of Asian adults;eLife;2023-09-14

5. Validation of Estimated Small Dense Low-Density Lipoprotein Cholesterol Concentration in a Japanese General Population;Journal of Atherosclerosis and Thrombosis;2023

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