AIMC Topic: Aged

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Eeg Microstates and Balance Parameters for Stroke Discrimination: A Machine Learning Approach.

Brain topography
Electroencephalography microstates (EEG-MS) show promise to be a neurobiological biomarker in stroke. Thus, the aim of the study was to identify biomarkers to discriminate stroke patients from healthy individuals based on EEG-MS and clinical features...

Ten Machine Learning Models for Predicting Preoperative and Postoperative Coagulopathy in Patients With Trauma: Multicenter Cohort Study.

Journal of medical Internet research
BACKGROUND: Recent research has revealed the potential value of machine learning (ML) models in improving prognostic prediction for patients with trauma. ML can enhance predictions and identify which factors contribute the most to posttraumatic morta...

Development and validation of a machine learning-based prediction model for hepatorenal syndrome in liver cirrhosis patients using MIMIC-IV and eICU databases.

Scientific reports
Hepatorenal syndrome (HRS) is a key contributor to poor prognosis in liver cirrhosis. This study aims to leverage the database to build a predictive model for early identification of high-risk patients. From two sizable public databases, we retrieved...

Development of a machine learning tool to predict deep inspiration breath hold requirement for locoregional right-sided breast radiation therapy patients.

Biomedical physics & engineering express
. This study presents machine learning (ML) models that predict if deep inspiration breath hold (DIBH) is needed based on lung dose in right-sided breast cancer patients during the initial computed tomography (CT) appointment.. Anatomic distances wer...

Gender-Equity Model for Liver Allocation Using Artificial Intelligence (GEMA-AI) for Waiting List Liver Transplant Prioritization.

Clinical gastroenterology and hepatology : the official clinical practice journal of the American Gastroenterological Association
BACKGROUND & AIMS: We aimed to develop and validate an artificial intelligence score (gender-equity model for liver allocation using artificial intelligence [GEMA-AI]) to predict liver transplantation (LT) waiting list outcomes using the same input v...

Contrast-enhanced ultrasound-based AI model for multi-classification of focal liver lesions.

Journal of hepatology
BACKGROUND & AIMS: Accurate multi-classification is a prerequisite for appropriate management of focal liver lesions (FLLs). Ultrasound is the most common imaging examination but lacks accuracy. Contrast-enhanced ultrasound (CEUS) offers better perfo...

Artificial intelligence-enhanced comprehensive assessment of the aortic valve stenosis continuum in echocardiography.

EBioMedicine
BACKGROUND: Transthoracic echocardiography (TTE) is the primary modality for diagnosing aortic stenosis (AS), yet it requires skilled operators and can be resource-intensive. We developed and validated an artificial intelligence (AI)-based system for...

Development of an artificial intelligence system to indicate intraoperative findings of scarring in laparoscopic cholecystectomy for cholecystitis.

Surgical endoscopy
BACKGROUND: The surgical difficulty of laparoscopic cholecystectomy (LC) for acute cholecystitis (AC) and the risk of bile duct injury (BDI) depend on the degree of fibrosis and scarring caused by inflammation; therefore, understanding these intraope...

Addressing Missing Data Challenges in Geriatric Health Monitoring: A Study of Statistical and Machine Learning Imputation Methods.

Sensors (Basel, Switzerland)
In geriatric healthcare, missing data pose significant challenges, especially in systems used for frailty monitoring in elderly individuals. This study explores advanced imputation techniques used to enhance data quality and maintain model performanc...