AIMC Topic: Aged

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AI-assisted 3D versus conventional 2D preoperative planning in total hip arthroplasty for Crowe type II-IV high hip dislocation: a two-year retrospective study.

Journal of orthopaedic surgery and research
BACKGROUND: With the growing complexity of total hip arthroplasty (THA) for high hip dislocation (HHD), artificial intelligence (AI)-assisted three-dimensional (3D) preoperative planning has emerged as a promising tool to enhance surgical accuracy. T...

Machine learning-assisted radiogenomic analysis for miR-15a expression prediction in renal cell carcinoma.

BMC cancer
BACKGROUND: Renal cell carcinoma (RCC) is a prevalent malignancy with highly variable outcomes. MicroRNA-15a (miR-15a) has emerged as a promising prognostic biomarker in RCC, linked to angiogenesis, apoptosis, and proliferation. Radiogenomics integra...

A smart secure virtual reality immersive application for alzheimer's and dementia patients.

Scientific reports
Alzheimer's disease (AD) poses significant challenges for the elderly, leading to cognitive decline, social isolation, and lower quality of life. Current interventions often require cumbersome wearable devices e.g. the camera-based monitoring that ma...

A development of machine learning models to preoperatively predict insufficient clinical improvement after total knee arthroplasty.

Journal of orthopaedic surgery and research
BACKGROUND: Identifying patients unlikely to achieve meaningful improvement following total knee arthroplasty (TKA) supports more effective shared decision-making (SDM). This study aimed to develop and validate machine learning (ML) models that preop...

Unsupervised clustering of biochemical markers reveals health profiles associated with function and survival in active aging.

Scientific reports
This study explores the relationships between biochemical phenotypes identified using machine learning, and key health outcomes, including body composition, physical function, and mortality risk. Data were collected from 536 physically active Spanish...

A study on the effectiveness of machine learning models for hepatitis prediction.

Scientific reports
Hepatitis continues to be a major global health challenge, leading to high morbidity and mortality rates. Despite advances in diagnosis and treatment, early prediction of hepatitis outcomes remains an essential area for improvement. This study seeks ...

Machine learning-based prediction model for post-stroke cerebral-cardiac syndrome: a risk stratification study.

Scientific reports
Cerebral-cardiac syndrome (CCS) is a severe cardiac complication following acute ischemic stroke, often associated with adverse outcomes. This study developed and validated a machine learning (ML) model to predict CCS using clinical, laboratory, and ...

Multimodal analysis of cell-free DNA enhances differentiation of early-stage breast cancer from benign lesions and healthy individuals.

BMC biology
BACKGROUND: Breast cancer (BC) remains the second leading cause of cancer-related mortality among women worldwide. Liquid biopsy based on circulating tumor DNA (ctDNA) offers a promising noninvasive approach for early detection; however, differentiat...

Optimizing timing and cost-effective use of plasma biomarkers in Alzheimer's disease.

Alzheimer's research & therapy
BACKGROUND AND OBJECTIVES: Early and cost-effective identification of amyloid positivity is crucial for Alzheimer's disease (AD) diagnosis. While amyloid PET is the gold standard, plasma biomarkers such as phosphorylated tau 217 (pTau217) provide a p...

Effect of discontinuing antipsychotic medications on the risk of hospitalization in long-term care: a machine learning-based analysis.

BMC medicine
BACKGROUND: Antipsychotic medications are frequently prescribed to older residents of long-term care facilities (LTCFs) despite their limited efficacy and considerable safety risks. While discontinuation of these drugs might help reduce their associa...