Ideal algorithms in healthcare: explainable, dynamic, precise, autonomous, fair, and reproducible

TJ Loftus, PJ Tighe, T Ozrazgat-Baslanti… - PLOS digital …, 2022 - journals.plos.org
Established guidelines describe minimum requirements for reporting algorithms in
healthcare; it is equally important to objectify the characteristics of ideal algorithms that …

Machine learning in precision diabetes care and cardiovascular risk prediction

EK Oikonomou, R Khera - Cardiovascular Diabetology, 2023 - Springer
Artificial intelligence and machine learning are driving a paradigm shift in medicine,
promising data-driven, personalized solutions for managing diabetes and the excess …

Machine learning–based models incorporating social determinants of health vs traditional models for predicting in-hospital mortality in patients with heart failure

MW Segar, JL Hall, PS Jhund, TM Powell-Wiley… - JAMA …, 2022 - jamanetwork.com
Importance Traditional models for predicting in-hospital mortality for patients with heart
failure (HF) have used logistic regression and do not account for social determinants of …

Development of an interpretable machine learning model associated with heavy metals' exposure to identify coronary heart disease among US adults via SHAP …

X Li, Y Zhao, D Zhang, L Kuang, H Huang, W Chen… - Chemosphere, 2023 - Elsevier
Limited information is available on the links between heavy metals' exposure and coronary
heart disease (CHD). We aim to establish an efficient and explainable machine learning …

The year in cardiovascular medicine 2021: digital health and innovation

PE Vardas, FW Asselbergs, M van Smeden… - European heart …, 2022 - academic.oup.com
This article presents some of the most important developments in the field of digital medicine
that have appeared over the last 12 months and are related to cardiovascular medicine. The …

Proteomics-enabled deep learning machine algorithms can enhance prediction of mortality

M Unterhuber, KP Kresoja, KP Rommel… - Journal of the American …, 2021 - jacc.org
Background Individualized risk prediction represents a prerequisite for providing
personalized medicine. Objectives This study compared proteomics-enabled machine …

Systematic analysis between inflammation-related index and sex hormones in American adults: cross-sectional research based NHANES 2013-2016

C Wei, W Zhang, J Chen, Q He, L Cao… - Frontiers in …, 2023 - frontiersin.org
Background A series of novel inflammation-related indexes has been confirmed to be
efficient indicators of human immune and inflammatory status, with great potential as …

Machine learning prediction of mortality in Acute Myocardial Infarction

M Oliveira, J Seringa, FJ Pinto, R Henriques… - BMC Medical Informatics …, 2023 - Springer
Abstract Background Acute Myocardial Infarction (AMI) is the leading cause of death in
Portugal and globally. The present investigation created a model based on machine …

Characteristics, process metrics, and outcomes among patients with ST-elevation myocardial infarction in rural vs urban areas in the US: a report from the US national …

D Hillerson, S Li, N Misumida, ZK Wegermann… - JAMA …, 2022 - jamanetwork.com
Importance Patients with ST-segment elevation myocardial infarction (STEMI) living in rural
settings often have worse clinical outcomes compared with their urban counterparts …

Adopting artificial intelligence in cardiovascular medicine: A scoping review

H Makimoto, T Kohro - Hypertension Research, 2024 - nature.com
Recent years have witnessed significant transformations in cardiovascular medicine, driven
by the rapid evolution of artificial intelligence (AI). This scoping review was conducted to …