AIMC Topic: Aged, 80 and over

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Machine learning for triage of strokes with large vessel occlusion using photoplethysmography biomarkers.

Physiological measurement
Objective.Large vessel occlusion (LVO) stroke presents a major challenge in clinical practice due to the potential for poor outcomes with delayed treatment. Treatment for LVO involves highly specialized care, in particular endovascular thrombectomy, ...

Mild Cognitive Impairment Detection System Based on Unstructured Spontaneous Speech: Longitudinal Dual-Modal Framework.

JMIR medical informatics
BACKGROUND: In recent years, the incidence of cognitive diseases has also risen with the significant increase in population aging. Among these diseases, Alzheimer disease constitutes a substantial proportion, placing a high-cost burden on health care...

Machine Learning Analysis of Retrospective Data From 503 Hospitalized Older Patients With Type 2 Diabetes to Identify Factors Associated With Cognitive Impairment.

Medical science monitor : international medical journal of experimental and clinical research
BACKGROUND Diabetes is increasingly prevalent among older adults; mild cognitive impairment (MCI) comorbidity in this group represents a major concern. Existing MCI prediction methods are often inaccurate, but machine learning (ML) offers improved po...

An Ultra-Brief Informant Questionnaire for Case Finding of Cognitive Impairment Across Diverse Literacy: Diagnostic Accuracy Study.

JMIR aging
BACKGROUND: Undiagnosed cognitive impairment poses a global challenge, prompting recent interest in ultra-brief screening questionnaires (comprising <2 to 3 items) to efficiently identify individuals needing further evaluation. However, evidence on u...

Construction and temporal external validation of interpretable machine-learning models for predicting tigecycline-associated hypofibrinogenemia.

European journal of clinical pharmacology
BACKGROUND AND PURPOSE: There is a paucity of available clinical tools with which to accurately predict the risk of tigecycline-associated hypofibrinogenemia, an adverse reaction with a high incidence and serious consequences. This study aimed to dev...

Artificial Intelligence-Enhanced Multi-Algorithm R Shiny Application for Predictive Modeling and Analytics: Case Study of Alzheimer Disease Diagnostics.

JMIR aging
BACKGROUND: Artificial intelligence (AI) has demonstrated superior diagnostic accuracy compared with medical practitioners, highlighting its growing importance in health care. SMART-Pred (Shiny Multi-Algorithm R Tool for Predictive Modeling) is an in...

Development of a machine learning-based model for predicting the functional outcome of patients with proximal femur fractures.

Scientific reports
Early-stage rehabilitation is crucial for the functional recovery of patients with proximal femur fractures. Predicting functional prognosis at such an early stage can simplify the process of planning for transfers and discharge destinations, as well...

Effects of bisphosphonates after denosumab discontinuation and treatment effect heterogeneity using causal machine learning.

Scientific reports
Discontinuation of denosumab is associated with a rebound increase in osteoporotic fracture (OF) risk, and bisphosphonates (BPs) are commonly recommended as sequential therapy to mitigate this risk. However, their real-world effectiveness-and whether...

Establishment of a postoperative delirium risk prediction model for elderly hip fracture patients based on machine learning algorithms.

BMC geriatrics
BACKGROUND: Although no definitive treatment exists, 30-40% of postoperative delirium cases are preventable through early risk identification and intervention. Therefore our aim was to develop and evaluate a postoperative delirium risk prediction mod...

Adherence to Accelerometer Use in Older Adults Undergoing mHealth Cardiac Rehabilitation: Secondary Analysis of a Randomized Clinical Trial.

Journal of medical Internet research
BACKGROUND: Wearable accelerometers, which continuously record physical activity metrics, are commonly used in mobile health-enabled cardiac rehabilitation (mHealth-CR). The association between adherence to accelerometer use during mHealth-CR and imp...