Artificial intelligence: practical primer for clinical research in cardiovascular disease

N Kagiyama, S Shrestha, PD Farjo… - Journal of the American …, 2019 - Am Heart Assoc
Artificial intelligence (AI) has begun to permeate and reform the field of medicine and
cardiovascular medicine. Impacting about 100 million patients in the United States, the …

Comparison of temporal and non-temporal features effect on machine learning models quality and interpretability for chronic heart failure patients

K Balabaeva, S Kovalchuk - Procedia Computer Science, 2019 - Elsevier
Chronic diseases are complex systems that can be described by various heteroscedastic
data that varies in time. The goal of this work is to determine whether historical data helps to …

Churn prediction using customers' implicit behavioral patterns and deep learning

A Tanveer - 2019 - research.sabanciuniv.edu
The processes of market globalization are rapidly changing the competitive conditions of the
business and financial sectors. With the emergence of new competitors and increasing …

SAVEHR: self attention vector representations for EHR based personalized chronic disease onset prediction and interpretability

S Mallya, M Overhage, S Bodapati, N Srivastava… - arXiv preprint arXiv …, 2019 - arxiv.org
Chronic disease progression is emerging as an important area of investment for healthcare
providers. As the quantity and richness of available clinical data continue to increase along …

[HTML][HTML] A Systematic Literature Review of Three Stenting Strategies for Bifurcation Lesions in Coronary Artery Disease

L Parsley-Raines, DM Brandt, DL Carr… - Journal of Health …, 2019 - ncbi.nlm.nih.gov
Background Bifurcation lesions represent 15–20% of all patients undergoing a
percutaneous coronary intervention (PCI) for coronary artery disease. The provisional 1 …