[HTML][HTML] Effective hospital readmission prediction models using machine-learned features
Background: Hospital readmissions are one of the costliest challenges facing healthcare
systems, but conventional models fail to predict readmissions well. Many existing models …
systems, but conventional models fail to predict readmissions well. Many existing models …
Predicting 30-day all-cause hospital readmission using multimodal spatiotemporal graph neural networks
Reduction in 30-day readmission rate is an important quality factor for hospitals as it can
reduce the overall cost of care and improve patient post-discharge outcomes. While deep …
reduce the overall cost of care and improve patient post-discharge outcomes. While deep …
[HTML][HTML] Predicting hospital readmission risk in patients with COVID-19: A machine learning approach
MR Afrash, H Kazemi-Arpanahi… - Informatics in medicine …, 2022 - Elsevier
Abstract Introduction The Coronavirus 2019 (COVID-19) epidemic stunned the health
systems with severe scarcities in hospital resources. In this critical situation, decreasing …
systems with severe scarcities in hospital resources. In this critical situation, decreasing …
Early prediction of high-cost inpatients with ischemic heart disease using network analytics and machine learning
P Yang, H Qiu, L Wang, L Zhou - Expert Systems with Applications, 2022 - Elsevier
Although identifying high-cost inpatients with ischemic heart disease (IHD) at the point of
admission is helpful for timely intervention and reducing costs, it is a difficult task due to the …
admission is helpful for timely intervention and reducing costs, it is a difficult task due to the …
A COVID-19 forecasting system for hospital needs using ANFIS and LSTM models: A graphical user interface unit
S Shafiekhani, P Namdar, S Rafiei - Digital Health, 2022 - journals.sagepub.com
Background Centers for Disease Control and Prevention data showed that about 40% of
coronavirus disease 2019 (COVID-19) patients had been suffering from at least one …
coronavirus disease 2019 (COVID-19) patients had been suffering from at least one …
[HTML][HTML] Forecasting hospital readmissions with machine learning
Hospital readmissions are regarded as a compounding economic factor for healthcare
systems. In fact, the readmission rate is used in many countries as an indicator of the quality …
systems. In fact, the readmission rate is used in many countries as an indicator of the quality …
[HTML][HTML] 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] Predicting 7-day unplanned readmission in elderly patients with coronary heart disease using machine learning
X Song, Y Tong, Y Luo, H Chang, G Gao… - Frontiers in …, 2023 - frontiersin.org
Background Short-term unplanned readmission is always neglected, especially for elderly
patients with coronary heart disease (CHD). However, tools to predict unplanned …
patients with coronary heart disease (CHD). However, tools to predict unplanned …
[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) …
[HTML][HTML] Predicting readmission charges billed by hospitals: machine learning approach
Background: The Centers for Medicare and Medicaid Services projects that health care
costs will continue to grow over the next few years. Rising readmission costs contribute …
costs will continue to grow over the next few years. Rising readmission costs contribute …