Smart technologies used as smart tools in the management of cardiovascular disease and their future perspective

M Ullah, S Hamayun, A Wahab, SU Khan… - Current Problems in …, 2023 - Elsevier
Cardiovascular disease (CVD) is a leading cause of morbidity and mortality worldwide. The
advent of smart technologies has significantly impacted the management of CVD, offering …

Performance of the Framingham risk models and pooled cohort equations for predicting 10-year risk of cardiovascular disease: a systematic review and meta-analysis

JA Damen, R Pajouheshnia, P Heus, KGM Moons… - BMC medicine, 2019 - Springer
Abstract Background The Framingham risk models and pooled cohort equations (PCE) are
widely used and advocated in guidelines for predicting 10-year risk of develo** coronary …

Risk prediction of covid-19 related death and hospital admission in adults after covid-19 vaccination: national prospective cohort study

J Hippisley-Cox, CAC Coupland, N Mehta, RH Keogh… - bmj, 2021 - bmj.com
Objectives To derive and validate risk prediction algorithms to estimate the risk of covid-19
related mortality and hospital admission in UK adults after one or two doses of covid-19 …

Living risk prediction algorithm (QCOVID) for risk of hospital admission and mortality from coronavirus 19 in adults: national derivation and validation cohort study

AK Clift, CAC Coupland, RH Keogh, K Diaz-Ordaz… - bmj, 2020 - bmj.com
Objective To derive and validate a risk prediction algorithm to estimate hospital admission
and mortality outcomes from coronavirus disease 2019 (covid-19) in adults. Design …

Development and validation of QRISK3 risk prediction algorithms to estimate future risk of cardiovascular disease: prospective cohort study

J Hippisley-Cox, C Coupland, P Brindle - bmj, 2017 - bmj.com
Objectives To develop and validate updated QRISK3 prediction algorithms to estimate the
10 year risk of cardiovascular disease in women and men accounting for potential new risk …

Deep survival analysis

R Ranganath, A Perotte… - Machine Learning for …, 2016 - proceedings.mlr.press
The electronic health record (EHR) provides an unprecedented opportunity to build
actionable tools to support physicians at the point of care. In this paper, we introduce deep …

Prediction and diagnosis of depression using machine learning with electronic health records data: a systematic review

D Nickson, C Meyer, L Walasek, C Toro - BMC medical informatics and …, 2023 - Springer
Background Depression is one of the most significant health conditions in personal, social,
and economic impact. The aim of this review is to summarize existing literature in which …

A systematic review of risk factors associated with depression and anxiety in cancer patients

D Ikhile, E Ford, D Glass, G Gremesty, H van Marwijk - Plos one, 2024 - journals.plos.org
Depression and anxiety are common comorbid conditions associated with cancer, however
the risk factors responsible for the onset of depression and anxiety in cancer patients are not …

High-risk prediction of cardiovascular diseases via attention-based deep neural networks

Y An, N Huang, X Chen, F Wu… - IEEE/ACM transactions …, 2019 - ieeexplore.ieee.org
High-risk prediction of cardiovascular disease is of great significance and impendency in
medical fields with the increasing phenomenon of sub-health these years. Most existing …

Creating fair models of atherosclerotic cardiovascular disease risk

S Pfohl, B Marafino, A Coulet, F Rodriguez… - Proceedings of the …, 2019 - dl.acm.org
Guidelines for the management of atherosclerotic cardiovascular disease (ASCVD)
recommend the use of risk stratification models to identify patients most likely to benefit from …