Machine learning methodologies versus cardiovascular risk scores, in predicting disease risk

被引：0

作者：

Alexandros C. Dimopoulos

Mara Nikolaidou

Francisco Félix Caballero

Worrawat Engchuan

Albert Sanchez-Niubo

Holger Arndt

José Luis Ayuso-Mateos

Josep Maria Haro

Somnath Chatterji

Ekavi N. Georgousopoulou

Christos Pitsavos

Demosthenes B. Panagiotakos

机构：

[1] Harokopio University,Department of Nutrition and Dietetics, School of Health Science and Education

[2] Harokopio University,Department of Informatics & Telematics, School of Digital Technology

[3] Universidad Autónoma de Madrid,Department of Preventive Medicine and Public Health

[4] CIBER of Epidemiology and Public Health,Hospital Universitario de La Princesa

[5] Instituto de Investigación Sanitaria Princesa (IP),The Centre for Applied Genomics, Genetics and Genome Biology

[6] The Hospital for Sick Children,Health Metrics and Measurement

[7] Parc Sanitari Sant Joan de Déu,Faculty of Health

[8] SPRING TECHNO GMBH & Co. KG,School of Medicine

[9] World Health Organization,undefined

[10] University of Canberra,undefined

[11] University of Athens,undefined

[12] CIBER of Mental Health,undefined

来源：

BMC Medical Research Methodology | / 18卷

关键词：

Cardiovascular disease; Risk prediction; Machine learning; Model performance;

D O I：

暂无

中图分类号：

学科分类号：

摘要：

引用

共 50 条

[21] Explainable machine learning framework for predicting long-term cardiovascular disease risk among adolescents
Haya Salah
Sharan Srinivas
Scientific Reports, 12
[22] Explainable machine learning framework for predicting long-term cardiovascular disease risk among adolescents
Salah, Haya
Srinivas, Sharan
SCIENTIFIC REPORTS, 2022, 12 (01)
[23] Machine Learning: Predicting Credit Risk
Melo, Rafael Almeida Pereira
Guimaraes, Paulo Henrique Sales
Melo, Marcel Irving Pereira
SIGMAE, 2024, 13 (04): : 219 - 230
[24] Cardiovascular Risk Prediction in Ankylosing Spondylitis: From Traditional Scores to Machine Learning Assessment
Luca Navarini
Francesco Caso
Luisa Costa
Damiano Currado
Liliana Stola
Fabio Perrotta
Lorenzo Delfino
Michela Sperti
Marco A. Deriu
Piero Ruscitti
Viktoriya Pavlych
Addolorata Corrado
Giacomo Di Benedetto
Marco Tasso
Massimo Ciccozzi
Alice Laudisio
Claudio Lunardi
Francesco Paolo Cantatore
Ennio Lubrano
Roberto Giacomelli
Raffaele Scarpa
Antonella Afeltra
Rheumatology and Therapy, 2020, 7 : 867 - 882
[25] Cardiovascular Risk Prediction in Ankylosing Spondylitis: From Traditional Scores to Machine Learning Assessment
Navarini, Luca
Caso, Francesco
Costa, Luisa
Currado, Damiano
Stola, Liliana
Perrotta, Fabio
Delfino, Lorenzo
Sperti, Michela
Deriu, Marco A.
Ruscitti, Piero
Pavlych, Viktoriya
Corrado, Addolorata
Di Benedetto, Giacomo
Tasso, Marco
Ciccozzi, Massimo
Laudisio, Alice
Lunardi, Claudio
Cantatore, Francesco Paolo
Lubrano, Ennio
Giacomelli, Roberto
Scarpa, Raffaele
Afeltra, Antonella
RHEUMATOLOGY AND THERAPY, 2020, 7 (04) : 867 - 882
[26] Cardiovascular Disease Risk Prediction Models and Scores
Giannakoulas, George
Doundoulakis, Ioannis
CURRENT PHARMACEUTICAL DESIGN, 2021, 27 (10) : 1231 - 1231
[27] Machine learning to predict cardiovascular risk
Quesada, Jose A.
Lopez-Pineda, Adriana
Gil-Guillen, Vicente F.
Durazo-Arvizu, Ramon
Orozco-Beltran, Domingo
Lopez-Domenech, Angela
Carratala-Munuera, Concepcion
INTERNATIONAL JOURNAL OF CLINICAL PRACTICE, 2019, 73 (10)
[28] Electronic health records and polygenic risk scores for predicting disease risk
Ruowang Li
Yong Chen
Marylyn D. Ritchie
Jason H. Moore
Nature Reviews Genetics, 2020, 21 : 493 - 502
[29] Electronic health records and polygenic risk scores for predicting disease risk
Li, Ruowang
Chen, Yong
Ritchie, Marylyn D.
Moore, Jason H.
NATURE REVIEWS GENETICS, 2020, 21 (08) : 493 - 502
[30] Polysocial Risk Scores: Implications for Cardiovascular Disease Risk Assessment and Management
Javed, Zulqarnain
Kundi, Harun
Chang, Ryan
Titus, Anoop
Arshad, Hassaan
CURRENT ATHEROSCLEROSIS REPORTS, 2023, 25 (12) : 1059 - 1068

← 1 2 3 4 5 →