AIMC Topic: Male

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Effects of Robot-Assisted Gait Training on Balance and Fear of Falling in Patients With Stroke: A Randomized Controlled Clinical Trial.

American journal of physical medicine & rehabilitation
OBJECTIVE: The aim of this study was compare the effects of combined training, which included robot-assisted gait training in addition to traditional balance training, and traditional balance training alone on balance and fear of falling in patients ...

PREDICTING IN-HOSPITAL MORTALITY IN CRITICAL ORTHOPEDIC TRAUMA PATIENTS WITH SEPSIS USING MACHINE LEARNING MODELS.

Shock (Augusta, Ga.)
Purpose: This study aims to establish and validate machine learning-based models to predict death in hospital among critical orthopedic trauma patients with sepsis or respiratory failure. Methods: This study collected 523 patients from the Medical In...

Explainable machine learning identifies a polygenic risk score as a key predictor of pancreatic cancer risk in the UK Biobank.

Digestive and liver disease : official journal of the Italian Society of Gastroenterology and the Italian Association for the Study of the Liver
BACKGROUND: Predicting the risk of developing pancreatic ductal adenocarcinoma (PDAC) is of paramount importance, given its high mortality rate. Current PDAC risk prediction models rely on a limited number of variables, do not include genetics, and h...

Research on mood monitoring and intervention for anxiety disorder patients based on deep learning wearable devices.

Technology and health care : official journal of the European Society for Engineering and Medicine
BackgroundAnxiety disorders are common mental health issues that have a significant effect on people's quality of life. Conventional techniques for tracking emotional states frequently lack the accuracy and sensitivity needed for successful intervent...

ChatGPT vs. surgeons on pancreatic cancer queries: accuracy & empathy evaluated by patients and experts.

HPB : the official journal of the International Hepato Pancreato Biliary Association
BACKGROUND: Artificial intelligence (AI) offers potential support in patient-clinician interactions, but its impact on such communication remains unexplored.

Tensor dictionary-based heterogeneous transfer learning to study emotion-related gender differences in brain.

Neural networks : the official journal of the International Neural Network Society
In practice, collecting auxiliary labeled data with same feature space from multiple domains is difficult. Thus, we focus on the heterogeneous transfer learning to address the problem of insufficient sample sizes in neuroimaging. Viewing subjects, ti...

A Machine learning classification framework using fused fractal property feature vectors for Alzheimer's disease diagnosis.

Brain research
Alzheimer's disease (AD) profoundly affects brain tissue and network structures. Analyzing the topological properties of these networks helps to understand the progression of the disease. Most studies focus on single-scale brain networks, but few add...

Machine learning in predicting cauda equina imaging outcomes- a solution to the problem.

European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society
PURPOSE: Cauda Equina Syndrome (CES) is a rare surgical emergency. The implications for loss of quality of life through delayed management are high, though no clinical symptom is pathognomonic in its diagnosis. We describe how machine learning based ...

Predictive analysis of COVID-19 occurrence and vaccination impacts across the 50 US states.

Computers in biology and medicine
OBJECTIVE: This study aimed to outline a machine learning model to assess the effectiveness of vaccination in COVID-19 confirmed cases and fatalities. The proposed model was evaluated using external validation to ensure optimal protection of vaccinat...