AI Medical Compendium Topic:
Aged, 80 and over

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Risk factors for prediabetes in community-dwelling adults: A generalized estimating equation logistic regression approach with natural language processing insights.

Research in nursing & health
The global prevalence of prediabetes is expected to reach 8.3% (587 million people) by 2045, with 70% of people with prediabetes developing diabetes during their lifetimes. We aimed to classify community-dwelling adults with a high risk for prediabet...

Predictive modeling for identification of older adults with high utilization of health and social services.

Scandinavian journal of primary health care
AIM: Machine learning techniques have demonstrated success in predictive modeling across various clinical cases. However, few studies have considered predicting the use of multisectoral health and social services among older adults. This research aim...

Predicting Alzheimer's disease from cognitive footprints in mid and late life: How much can register data and machine learning help?

International journal of medical informatics
BACKGROUND: Real-world data with decades-long medical records are increasingly available alongside the growing adoption of machine learning in healthcare research. We evaluated the performance of machine learning models in predicting the risk of Alzh...

Super-resolution deep learning reconstruction approach for enhanced visualization in lumbar spine MR bone imaging.

European journal of radiology
OBJECTIVES: This study aims to assess the effectiveness of super-resolution deep-learning-based reconstruction (SR-DLR), which leverages k-space data, on the image quality of lumbar spine magnetic resonance (MR) bone imaging using a 3D multi-echo in-...

An artificial intelligence system for comprehensive pathologic outcome prediction in early gastric cancer through endoscopic image analysis (with video).

Gastric cancer : official journal of the International Gastric Cancer Association and the Japanese Gastric Cancer Association
BACKGROUND: Accurate prediction of pathologic results for early gastric cancer (EGC) based on endoscopic findings is essential in deciding between endoscopic and surgical resection. This study aimed to develop an artificial intelligence (AI) model to...

Predicting recovery following stroke: Deep learning, multimodal data and feature selection using explainable AI.

NeuroImage. Clinical
Machine learning offers great potential for automated prediction of post-stroke symptoms and their response to rehabilitation. Major challenges for this endeavour include the very high dimensionality of neuroimaging data, the relatively small size of...

Fully Automatic Deep Learning Model for Spine Refracture in Patients with OVCF: A Multi-Center Study.

Orthopaedic surgery
BACKGROUND: The reaserch of artificial intelligence (AI) model for predicting spinal refracture is limited to bone mineral density, X-ray and some conventional laboratory indicators, which has its own limitations. Besides, it lacks specific indicator...

Development and Validation of a Machine Learning Algorithm to Predict the Risk of Blood Transfusion after Total Hip Replacement in Patients with Femoral Neck Fractures: A Multicenter Retrospective Cohort Study.

Orthopaedic surgery
OBJECTIVE: Total hip arthroplasty (THA) remains the primary treatment option for femoral neck fractures in elderly patients. This study aims to explore the risk factors associated with allogeneic blood transfusion after surgery and to develop a dynam...

Deep learning analysis for differential diagnosis and risk classification of gastrointestinal tumors.

Scandinavian journal of gastroenterology
OBJECTIVES: Recently, artificial intelligence (AI) has been applied to clinical diagnosis. Although AI has already been developed for gastrointestinal (GI) tract endoscopy, few studies have applied AI to endoscopic ultrasound (EUS) images. In this st...