AIMC Topic: Middle Aged

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Prediction of the functional outcome of intensive inpatient rehabilitation after stroke using machine learning methods.

Scientific reports
An accurate and reliable functional prognosis is vital to stroke patients addressing rehabilitation, to their families, and healthcare providers. This study aimed at developing and validating externally patient-wise prognostic models of the global fu...

Using a Robot to Address the Well-Being, Social Isolation, and Loneliness of Care Home Residents via Video Calls: Qualitative Feasibility Study.

JMIR formative research
BACKGROUND: About 40,000 people are living in Norwegian care homes, where a majority are living with a dementia diagnosis. Social isolation and loneliness are common issues affecting care home residents' quality of life. Due to visitation restriction...

Optimizing the dynamic treatment regime of outpatient rehabilitation in patients with knee osteoarthritis using reinforcement learning.

Journal of neuroengineering and rehabilitation
BACKGROUND: Knee osteoarthritis (KOA) is a prevalent chronic disease worldwide, and traditional treatment methods lack personalized adjustment for individual patient differences and cannot meet the needs of personalized treatment.

Validation of artificial intelligence algorithm LuxIA for screening of diabetic retinopathy from a single 45° retinal colour fundus images: the CARDS study.

BMJ open ophthalmology
OBJECTIVE: This study validated the artificial intelligence (AI)-based algorithm LuxIA for screening more-than-mild diabetic retinopathy (mtmDR) from a single 45° colour fundus image of patients with diabetes mellitus (DM, type 1 or type 2) in Spain....

Identifying most important predictors for suicidal thoughts and behaviours among healthcare workers active during the Spain COVID-19 pandemic: a machine-learning approach.

Epidemiology and psychiatric sciences
AIMS: Studies conducted during the COVID-19 pandemic found high occurrence of suicidal thoughts and behaviours (STBs) among healthcare workers (HCWs). The current study aimed to (1) develop a machine learning-based prediction model for future STBs us...

Hierarchical diagnosis of breast phyllodes tumors enabled by deep learning of ultrasound images: a retrospective multi-center study.

Cancer imaging : the official publication of the International Cancer Imaging Society
OBJECTIVE: Phyllodes tumors (PTs) are rare breast tumors with high recurrence rates, current methods relying on post-resection pathology often delay detection and require further surgery. We propose a deep-learning-based Phyllodes Tumors Hierarchical...

Hearing vocals to recognize schizophrenia: speech discriminant analysis with fusion of emotions and features based on deep learning.

BMC psychiatry
BACKGROUND AND OBJECTIVE: Accurate detection of schizophrenia poses a grand challenge as a complex and heterogeneous mental disorder. Current diagnostic criteria rely primarily on clinical symptoms, which may not fully capture individual differences ...

EEG-based Signatures of Schizophrenia, Depression, and Aberrant Aging: A Supervised Machine Learning Investigation.

Schizophrenia bulletin
BACKGROUND: Electroencephalography (EEG) is a noninvasive, cost-effective, and robust tool, which directly measures in vivo neuronal mass activity with high temporal resolution. Combined with state-of-the-art machine learning (ML) techniques, EEG rec...

Evaluating the impact of AI-generated educational content on patient understanding and anxiety in endodontics and restorative dentistry: a comparative study.

BMC oral health
BACKGROUND: Effective patient education is critical in enhancing treatment outcomes and reducing anxiety in dental procedures. This study compares the effectiveness of AI-generated educational materials with traditional methods in improving patient c...

Comparing Artificial Intelligence-Generated and Clinician-Created Personalized Self-Management Guidance for Patients With Knee Osteoarthritis: Blinded Observational Study.

Journal of medical Internet research
BACKGROUND: Knee osteoarthritis is a prevalent, chronic musculoskeletal disorder that impairs mobility and quality of life. Personalized patient education aims to improve self-management and adherence; yet, its delivery is often limited by time const...