AI Medical Compendium Topic

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Acute Disease

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Predictive Analytics for Care and Management of Patients With Acute Diseases: Deep Learning-Based Method to Predict Crucial Complication Phenotypes.

Journal of medical Internet research
BACKGROUND: Acute diseases present severe complications that develop rapidly, exhibit distinct phenotypes, and have profound effects on patient outcomes. Predictive analytics can enhance physicians' care and management of patients with acute diseases...

Early identification of patients with acute gastrointestinal bleeding using natural language processing and decision rules.

Journal of gastroenterology and hepatology
BACKGROUND AND AIM: Guidelines recommend risk stratification scores in patients presenting with gastrointestinal bleeding (GIB), but such scores are uncommonly employed in practice. Automation and deployment of risk stratification scores in real time...

Artificial intelligence in biliopancreatic endoscopy: Is there any role?

Best practice & research. Clinical gastroenterology
Artificial intelligence (AI) research in endoscopy is being translated at rapid pace with a number of approved devices now available for use in luminal endoscopy. However, the published literature for AI in biliopancreatic endoscopy is predominantly ...

Acute hyperglycaemia in cystic fibrosis pulmonary exacerbations.

Endocrinology, diabetes & metabolism
BACKGROUND: Hyperglycaemia may contribute to failure to recover from pulmonary exacerbations in cystic fibrosis (CF). We aimed to evaluate the prevalence and mechanism of hyperglycaemia during and post-exacerbations.

Separability of Acute Cerebral Infarction Lesions in CT Based Radiomics: Toward Artificial Intelligence-Assisted Diagnosis.

BioMed research international
This study aims at analyzing the separability of acute cerebral infarction lesions which were invisible in CT. 38 patients, who were diagnosed with acute cerebral infarction and performed both CT and MRI, and 18 patients, who had no positive finding ...

The opportunities and challenges of machine learning in the acute care setting for precision prevention of posttraumatic stress sequelae.

Experimental neurology
Personalized medicine is among the most exciting innovations in recent clinical research, offering the opportunity for tailored screening and management at the individual level. Biomarker-enriched clinical trials have shown increased efficiency and i...

The Challenges of Implementing Artificial Intelligence into Surgical Practice.

World journal of surgery
BACKGROUND: Artificial intelligence is touted as the future of medicine. Classical algorithms for the detection of common bile duct stones (CBD) have had poor clinical uptake due to low accuracy. This study explores the challenges of developing and i...

Explainable artificial intelligence model to predict acute critical illness from electronic health records.

Nature communications
Acute critical illness is often preceded by deterioration of routinely measured clinical parameters, e.g., blood pressure and heart rate. Early clinical prediction is typically based on manually calculated screening metrics that simply weigh these pa...

Recurrent probabilistic neural network-based short-term prediction for acute hypotension and ventricular fibrillation.

Scientific reports
In this paper, we propose a novel method for predicting acute clinical deterioration triggered by hypotension, ventricular fibrillation, and an undiagnosed multiple disease condition using biological signals, such as heart rate, RR interval, and bloo...

A novel and simple machine learning algorithm for preoperative diagnosis of acute appendicitis in children.

Pediatric surgery international
INTRODUCTION: There is a tendency toward nonoperative management of appendicitis resulting in an increasing need for preoperative diagnosis and classification. For medical purposes, simple conceptual decision-making models that can learn are widely u...