AIMC Topic: Acute Disease

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A Soft Computing Approach to Kidney Diseases Evaluation.

Journal of medical systems
Kidney renal failure means that one's kidney have unexpectedly stopped functioning, i.e., once chronic disease is exposed, the presence or degree of kidney dysfunction and its progression must be assessed, and the underlying syndrome has to be diagno...

Prediction of Outcome in Acute Lower Gastrointestinal Bleeding Using Gradient Boosting.

PloS one
BACKGROUND: There are no widely used models in clinical care to predict outcome in acute lower gastro-intestinal bleeding (ALGIB). If available these could help triage patients at presentation to appropriate levels of care/intervention and improve me...

A medical cost estimation with fuzzy neural network of acute hepatitis patients in emergency room.

Computer methods and programs in biomedicine
Taiwan is an area where chronic hepatitis is endemic. Liver cancer is so common that it has been ranked first among cancer mortality rates since the early 1980s in Taiwan. Besides, liver cirrhosis and chronic liver diseases are the sixth or seventh i...

Clinical phenotypes and risk of early hemodynamic deterioration in intermediate-high-risk patients with acute pulmonary embolism.

Thrombosis research
INTRODUCTION: Intermediate-high-risk pulmonary embolism (PE) patients face elevated risks of sudden clinical deterioration in early hours after symptoms onset. We performed a hierarchical cluster analysis among intermediate-high risk PE patients to i...

A machine learning approach for assessing acute infection by erythrocyte sedimentation rate (ESR) kinetics.

Clinica chimica acta; international journal of clinical chemistry
BACKGROUND: The erythrocyte sedimentation rate (ESR) is a traditional marker of inflammation, valued for its simplicity and low cost but limited by unsatisfactory specificity and sensitivity. This study evaluated the equivalence of ESR measurements o...

A Deep Learning Model for Identifying the Risk of Mesenteric Malperfusion in Acute Aortic Dissection Using Initial Diagnostic Data: Algorithm Development and Validation.

Journal of medical Internet research
BACKGROUND: Mesenteric malperfusion (MMP) is an uncommon but devastating complication of acute aortic dissection (AAD) that combines 2 life-threatening conditions-aortic dissection and acute mesenteric ischemia. The complex pathophysiology of MMP pos...

Machine learning models for predicting in-hospital mortality from acute pancreatitis in intensive care unit.

BMC medical informatics and decision making
BACKGROUND: Acute pancreatitis (AP) represents a critical medical condition where timely and precise prediction of in-hospital mortality is crucial for guiding optimal clinical management. This study focuses on the development of advanced machine lea...

A predictive model for hospital death in cancer patients with acute pulmonary embolism using XGBoost machine learning and SHAP interpretation.

Scientific reports
The prediction of in-hospital mortality in cancer patients with acute pulmonary embolism (APE) remains a significant clinical challenge. This study aimed to develop and validate a machine learning model using XGBoost to predict in-hospital mortality ...

Deep learning-based automatic differentiation of acute angle closure with or without zonulopathy using ultrasound biomicroscopy: a comparison of diagnostic performance with ophthalmologists.

BMJ open ophthalmology
OBJECTIVE: This study aims to develop ultrasound biomicroscopy (UBM)-based artificial intelligence (AI) models for preoperative differentiation of acute angle closure (AAC) with or without zonulopathy and to compare their comprehensive diagnostic per...