A survey on AI techniques for thoracic diseases diagnosis using medical images
Thoracic diseases refer to disorders that affect the lungs, heart, and other parts of the rib
cage, such as pneumonia, novel coronavirus disease (COVID-19), tuberculosis …
cage, such as pneumonia, novel coronavirus disease (COVID-19), tuberculosis …
Deep learning-enabled technologies for bioimage analysis
Deep learning (DL) is a subfield of machine learning (ML), which has recently demonstrated
its potency to significantly improve the quantification and classification workflows in …
its potency to significantly improve the quantification and classification workflows in …
Applications of machine learning in cardiology
K Seetharam, S Balla, C Bianco, J Cheung… - Cardiology and …, 2022 - Springer
In this digital era, artificial intelligence (AI) is establishing a strong foothold in commercial
industry and the field of technology. These effects are trickling into the healthcare industry …
industry and the field of technology. These effects are trickling into the healthcare industry …
Machine learning–based 30-day readmission prediction models for patients with heart failure: a systematic review
MY Yu, YJ Son - European Journal of Cardiovascular Nursing, 2024 - academic.oup.com
Aims Heart failure (HF) is one of the most frequent diagnoses for 30-day readmission after
hospital discharge. Nurses have role in reducing unplanned readmission and providing …
hospital discharge. Nurses have role in reducing unplanned readmission and providing …
Predicting unplanned readmission due to cardiovascular disease in hospitalized patients with cancer: a machine learning approach
Cardiovascular disease (CVD) in cancer patients can affect the risk of unplanned
readmissions, which have been reported to be costly and associated with worse mortality …
readmissions, which have been reported to be costly and associated with worse mortality …
[HTML][HTML] Comparison of machine learning algorithms for predicting hospital readmissions and worsening heart failure events in patients with heart failure with reduced …
Background Heart failure (HF) is highly prevalent in the United States. Approximately one-
third to one-half of HF cases are categorized as HF with reduced ejection fraction (HFrEF) …
third to one-half of HF cases are categorized as HF with reduced ejection fraction (HFrEF) …
Predictive Modeling for Hospital Readmissions for Patients with Heart Disease: An updated review from 2012-2023
W Zhang, W Cheng, K Fujiwara… - IEEE Journal of …, 2024 - ieeexplore.ieee.org
Hospital readmissions are a major concern for healthcare leaders, policy makers, and
patients, resulting in adverse health outcomes and imposing an increased burden on …
patients, resulting in adverse health outcomes and imposing an increased burden on …
Predicting 30-day readmission for stroke using machine learning algorithms: a prospective cohort study
YC Chen, JH Chung, YJ Yeh, SJ Lou, HF Lin… - Frontiers in …, 2022 - frontiersin.org
Background Machine learning algorithms for predicting 30-day stroke readmission are rarely
discussed. The aims of this study were to identify significant predictors of 30-day …
discussed. The aims of this study were to identify significant predictors of 30-day …
Machine learning to identify chronic cough from administrative claims data
V Bali, V Turzhitsky, J Schelfhout, M Paudel… - Scientific Reports, 2024 - nature.com
Accurate identification of patient populations is an essential component of clinical research,
especially for medical conditions such as chronic cough that are inconsistently defined and …
especially for medical conditions such as chronic cough that are inconsistently defined and …
Artificial intelligence's role in vascular surgery decision-making
DS Zarkowsky, DP Stonko - Seminars in Vascular Surgery, 2021 - Elsevier
Artificial intelligence (AI) is the next great advance informing medical science. Several
disciplines, including vascular surgery, use AI-based decision-making tools to improve …
disciplines, including vascular surgery, use AI-based decision-making tools to improve …