AIMC Topic: Retrospective Studies
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Radiomics-based MRI model to predict hypoperfusion in lacunar infarction.
Magnetic resonance imaging
Mar 21, 2025
BACKGROUND: Approximately 20-30 % of patients with acute ischemic stroke due to lacunar infarction experience early neurological deterioration (END) within the first three days after onset, leading to disability or more severe sequelae. Hemodynamic p...
Measurement of adipose body composition using an artificial intelligence-based CT Protocol and its association with severe acute pancreatitis in hospitalized patients.
Digestive and liver disease : official journal of the Italian Society of Gastroenterology and the Italian Association for the Study of the Liver
Mar 21, 2025
BACKGROUND/OBJECTIVES: The clinical utility of body composition in predicting the severity of acute pancreatitis (AP) remains unclear. We aimed to measure body composition using artificial intelligence (AI) to predict severe AP in hospitalized patien...
Machine learning-based risk prediction model for neuropathic foot ulcers in patients with diabetic peripheral neuropathy.
Journal of diabetes investigation
Mar 21, 2025
BACKGROUND: Diabetic peripheral neuropathy (DPN) is a common chronic complication of diabetes, marked by symptoms like hyperalgesia, numbness, and swelling that impair quality of life. Nerve conduction abnormalities in DPN significantly increase the ...
Application of machine learning models to identify predictors of good outcome after laparoscopic fundoplication.
Journal of gastrointestinal surgery : official journal of the Society for Surgery of the Alimentary Tract
Mar 21, 2025
BACKGROUND: Laparoscopic fundoplication remains the gold standard treatment for gastroesophageal reflux disease. However, 10% to 20% of patients experience new, persistent, or recurrent symptoms warranting further treatment. Potential predictors for ...
A risk prediction model for gastric cancer based on endoscopic atrophy classification.
BMC cancer
Mar 21, 2025
BACKGROUNDS: Gastric cancer (GC) is a prevalent malignancy affecting the digestive system. We aimed to develop a risk prediction model based on endoscopic atrophy classification for GC.
Development and validation of a machine learning-based nomogram for predicting prognosis in lung cancer patients with malignant pleural effusion.
Scientific reports
Mar 21, 2025
Malignant pleural effusion (MPE) is a common complication in patients with advanced lung cancer, significantly impacting their survival rates and quality of life. Effective tools for assessing the prognosis of these patients are urgently needed to en...
Can Artificial Intelligence Software be Utilised for Thyroid Multi-Disciplinary Team Outcomes?
Clinical otolaryngology : official journal of ENT-UK ; official journal of Netherlands Society for Oto-Rhino-Laryngology & Cervico-Facial Surgery
Mar 20, 2025
OBJECTIVES: ChatGPT is one of the most publicly available artificial intelligence (AI) softwares. Ear, nose and throat (ENT) services are often stretched due to the increasing incidence of thyroid malignancies. This study aims to investigate whether ...
Using Machine Learning to Identify Social Determinants of Health that Impact Discharge Disposition for Hospitalized Patients.
Journal of the American Medical Directors Association
Mar 20, 2025
OBJECTIVE: To identify self-reported social determinants of health (SDOH) among hospitalized patients that predict discharge to a skilled nursing facility (SNF).
A machine learning model based on placental magnetic resonance imaging and clinical factors to predict fetal growth restriction.
BMC pregnancy and childbirth
Mar 20, 2025
OBJECTIVES: To create a placental radiomics-clinical machine learning model to predict FGR.
Predicting postoperative nausea and vomiting using machine learning: a model development and validation study.
BMC anesthesiology
Mar 20, 2025
BACKGROUND: Postoperative nausea and vomiting (PONV) is a frequently observed complication in patients undergoing surgery under general anesthesia. Moreover, it is a frequent cause of distress and dissatisfaction in the early postoperative period. Cu...
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