Geriatrics

Development of an explainable machine learning model to reproduce and interpret expert pharmacological decisions in osteoporosis treatment.

The management of osteoporosis in real-world clinical practice is highly heterogeneous, reflecting the complexity and variability inherent in therapeutic decision-making. Although artificial intelligence (AI)-based tools have been developed to support diagnosis, limited research has investigated their potential to elucidate the rationale underlying treatment choices. This study applied explainable...

Unveiling CDKN1A and RELA: Machine learning-driven aging biomarkers for precision diagnosis and therapy in knee osteoarthritis.

BACKGROUND: Knee Osteoarthritis (KOA) is a degenerative joint disease marked by progressive cartilage deterioration, closely tied to cellular senescence. Despite advances in understanding KOA mechanisms, systematically identifying aging-related biomarkers remains challenging. METHODS: KOA gene expression datasets (GSE12021, GSE169077) were sourced from the GEO database, and aging-related genes fro...

Diabetes-linked metabolic dysfunction relates with distinct tau phosphorylation patterns, neuroinflammation and cognitive impairment in mouse models of Alzheimer's disease.

Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by amyloid-β plaques and tau neurofibrillary tangles, with tau path...

A Causal Validation augmented Temporal Convolutional Framework for Brain Effective Connectivity Networks Estimation.

Advancements in neuroimaging have facilitated unprecedented insights into brain connectivity, making the study of brain effective connectivity network...

QENNA: A quantum-enhanced neural network for early Alzheimer's detection using magnetic resonance imaging.

Early detection of Alzheimer's disease (AD) is essential for effective clinical intervention and disease management. However, conventional Deep Learni...

Secretary or SecretarAI: assessing the triage performance of AI vs human staff in a specialized dental clinic.

OBJECTIVE: Effective patient triage in specialized clinics is crucial for managing long waiting lists and mitigating clinical risk. This is often perf...

Anomaly changes in the functional connectome of post-operative neurosurgical patients: A case series.

PURPOSE: The use of neuronavigation with superimposed mapping tools has enabled visualization of key fiber tracts and improved peri-operative planning...

Emerging risk factors for stroke and bleeding in patients with atrial fibrillation and heart failure-a narrative review.

Atrial fibrillation (AF) and heart failure (HF) frequently coexist, which leads to adverse clinical outcomes and a significant increase in the risk of...

Machine Learning Algorithms for Predicting Injurious Fall Risk Among Older Adults With Depression: A Prognostic Modeling Study.

BACKGROUND: Falls and related injuries (FRI) pose a large burden among older adults with depression. Proactively identifying individuals at high FRI r...

Artificial intelligence and transplanting the elderly.

PURPOSE OF REVIEW: The integration of artificial intelligence into allocation, organ retrieval and transplantation processes represents an innovative ...

Automated Recognition and Measurement for Levator Hiatus in 3D Ultrasound: A Clinical Study in Postpartum Women.

OBJECTIVES: To evaluate the performance of a CNN-based (convolutional neural networks-based) AI software for automatic recognition and measurement of ...

Delineating white matter phenotypes of sensori-/psychomotor functioning in large-scale cohorts of healthy individuals and patients with mental disorders across the lifespan (whiteSPAN): rationale and methods of an interdisciplinary bicentric project.

Aberrant sensori-/psychomotor functioning-including muscular hand weakness, sedentary behavior, psychomotor agitation, slowing, agitation, apathy, and...

Artificial Intelligence Technologies Supporting Nurses' Clinical Decision-Making: A Systematic Review.

BACKGROUND: The use of technology to support nurses' decision-making is increasing in response to growing healthcare demands. AI, a global trend, hold...

Identification of common genetic features and pathways for osteoporosis with frozen shoulder by integrated bioinformatics analysis and machine learning.

Frozen shoulder (FS) and osteoporosis (OP) are common age-related degenerative diseases, occurring more frequently in females, which suggests potentia...

Mortality prediction among older people in primary care: a comparison of predictive performance of the frailty index with regression-based and machine learning models.

INTRODUCTION: The frailty index is widely used to identify vulnerable individuals at risk of adverse outcomes like mortality. However, its predictive ...

Attention-based deep learning for immunoglobulin typing from electrophoresis and laboratory data.

BACKGROUND: Interpretation of immunotyping results from serum protein electrophoresis (SPE) remains labor-intensive and subject to inter-observer vari...

Multi-view subspace tensorization with attentive clustering embedding.

Deep learning-based multi-view clustering (DMVC) has garnered significant attention and achieved remarkable success, primarily due to its powerful non...

Deep learning based CT grading system for sacroiliitis: a multi-center studydemonstrating superior accuracy and efficiency compared to human readers.

BACKGROUND: To develop and validate a deep convolutional neural network (DCNN) for automated sacroiliitis grading in axial spondyloarthritis (axSpA) u...

Machine learning pipeline for automated segmentation and classification of complicated cystic renal masses on MRI: comparison with radiologists' assessments.

PURPOSE: To develop and validate a machine learning (ML)-based pipeline for automated segmentation and classification of complicated cystic renal mass...

Bridging the Hearing Divide: Policy Solutions for Aging Americans.

Hearing loss affects approximately two thirds of adults in the United States aged 70 years or older and frequently remains untreated despite its well-...