AIMC Topic: Acute Disease
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Application Value of the Automated Machine Learning Model Based on Modified Computed Tomography Severity Index Combined With Serological Indicators in the Early Prediction of Severe Acute Pancreatitis.
Journal of clinical gastroenterology
Aug 1, 2024
BACKGROUND AND AIMS: Machine learning (ML) algorithms are widely applied in building models of medicine due to their powerful studying and generalizing ability. To assess the value of the Modified Computed Tomography Severity Index (MCTSI) combined w...
Comparison of machine learning and conventional statistical modeling for predicting readmission following acute heart failure hospitalization.
American heart journal
Jul 31, 2024
INTRODUCTION: Developing accurate models for predicting the risk of 30-day readmission is a major healthcare interest. Evidence suggests that models developed using machine learning (ML) may have better discrimination than conventional statistical mo...
Identification of severe acute pediatric asthma phenotypes using unsupervised machine learning.
Pediatric pulmonology
Jul 29, 2024
RATIONALE: More targeted management of severe acute pediatric asthma could improve clinical outcomes.
Multimodal deep learning models utilizing chest X-ray and electronic health record data for predictive screening of acute heart failure in emergency department.
Computer methods and programs in biomedicine
Jul 29, 2024
BACKGROUND AND OBJECTIVES: Ambiguity in diagnosing acute heart failure (AHF) leads to inappropriate treatment and potential side effects of rescue medications. To address this issue, this study aimed to use multimodality deep learning models combinin...
Deep learning for predicting rehospitalization in acute heart failure: Model foundation and external validation.
ESC heart failure
Jul 9, 2024
AIMS: Assessing the risk for HF rehospitalization is important for managing and treating patients with HF. To address this need, various risk prediction models have been developed. However, none of them used deep learning methods with real-world data...
Factors of acute respiratory infection among under-five children across sub-Saharan African countries using machine learning approaches.
Scientific reports
Jul 9, 2024
Symptoms of Acute Respiratory infections (ARIs) among under-five children are a global health challenge. We aimed to train and evaluate ten machine learning (ML) classification approaches in predicting symptoms of ARIs reported by mothers among child...
Artificial Intelligence-Based Electrocardiographic Biomarker for Outcome Prediction in Patients With Acute Heart Failure: Prospective Cohort Study.
Journal of medical Internet research
Jul 3, 2024
BACKGROUND: Although several biomarkers exist for patients with heart failure (HF), their use in routine clinical practice is often constrained by high costs and limited availability.
Multicenter validation of an artificial intelligence (AI)-based platform for the diagnosis of acute appendicitis.
Surgery
Jun 22, 2024
BACKGROUND: The current scores used to help diagnose acute appendicitis have a "gray" zone in which the diagnosis is usually inconclusive. Furthermore, the universal use of CT scanning is limited because of the radiation hazards and/or limited resour...
A deep learning-powered diagnostic model for acute pancreatitis.
BMC medical imaging
Jun 20, 2024
BACKGROUND: Acute pancreatitis is one of the most common diseases requiring emergency surgery. Rapid and accurate recognition of acute pancreatitis can help improve clinical outcomes. This study aimed to develop a deep learning-powered diagnostic mod...
Machine learning algorithms to predict healthcare-seeking behaviors of mothers for acute respiratory infections and their determinants among children under five in sub-Saharan Africa.
Frontiers in public health
Jun 19, 2024
BACKGROUND: Acute respiratory infections (ARIs) are the leading cause of death in children under the age of 5 globally. Maternal healthcare-seeking behavior may help minimize mortality associated with ARIs since they make decisions about the kind and...
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