Menopause

Repurposing Non-oncologic Drugs via Targeted Nanocarriers for Cancer Therapy: Mechanisms, Synergistic Combinations, and Clinical Translation.

The urgent need for innovative cancer therapies has driven increasing interest in repurposing drugs originally developed for non-oncological diseases. Several FDA-approved and clinically investigated agents, including mesalamine, celecoxib, gliclazide, metformin, itraconazole, and doxycycline, have shown anticancer potential through diverse mechanisms. However, despite their therapeutic potential,...

Reinforcement learning-driven adaptive game therapy for cognitive impairment patients with improved vision transformer based detection model.

BACKGROUND: Cognitive impairment is the growing challenge that requires early diagnosis and personalized management of neurodegenerative conditions like Alzheimer's disease. Neuroimaging modalities like Magnetic Resonance Imaging (MRI) provide valuable structural and functional insights into brain changes associated with cognitive decline. However, existing deep learning (DL) based diagnostic mode...

Microfluidic-electrochemical sweat patches for athletes: monitoring lactate, electrolytes, and hydration status.

Wearable biochemical sensing is shifting sports physiology from intermittent laboratory sampling toward continuous, in situ readouts during training a...

Metabolic and vascular outcomes after transition to the MiniMed 780G system in adults ≥65 years with type 1 diabetes: a randomised, single-centre study.

AIMS/HYPOTHESIS: Hybrid closed-loop insulin delivery systems are increasingly regarded as the preferred therapy for type 1 diabetes, although evidence...

Serial OCT-based coronary physiology and plaque composition in vessels with nonobstructive coronary lesions following intensive lipid-lowering therapy: YELLOW III sub-study.

BACKGROUND AND AIMS: Non-obstructive coronary plaques are a major source of future coronary events, particularly when characterized by high lipid burd...

Viral Infections and Neurodegenerative Diseases: Reinterpreting the Crosstalk Through a Dual-Role Lens.

Neurodegenerative diseases (NDDs) are multifactorial disorders with increasing evidence implicating viral infections in their pathogenesis. However, c...

Exploring Non-Embodied AI-Based Digital Companions for Older Adults in Aging and Care Contexts: Protocol for a Scoping Review.

BACKGROUND: Conversational artificial intelligence (AI) technologies are increasingly positioned as a response to social isolation, loneliness, and un...

Leveraging simulation to provide a practical framework for estimating the novel scope of risk of large language models in healthcare.

BACKGROUND: Large language models (LLMs) are rapidly entering clinical and consumer use, yet their probabilistic outputs have delivered a variety of u...

Identification of key predictors of postmenopausal osteoporosis from routine clinical indicators using explainable machine learning.

BACKGROUND: Machine learning (ML) shows promise in using clinical data to predict chronic diseases. However, its application in PMOP risk assessment u...

Wearable electrochemical biosensors for sweat uric acid detection: next generation technology for personalised healthcare.

Uric acid (UA) is a critical endogenous metabolite that contributes to the regulation of various physiological functions essential for maintaining hom...

Integrating neurobiological markers to prospectively predict adolescent non-suicidal self-injury and suicide attempts: a machine learning approach.

BACKGROUND: Suicide attempts (SA) and non-suicidal self-injury (NSSI) are closely related phenomena, both common in adolescent clinical samples. This ...

Kernel PCA for out-of-Distribution Detection: Non-Linear Kernel Selection and Approximation.

Out-of-Distribution (OoD) detection is vital for the reliability of deep neural networks, the key of which lies in effectively characterizing the disp...

Efficacy and Hepatotoxicity of Psoralea corylifolia L.: A Meta-Analysis and Machine Learning Assessment in Postmenopausal Osteoporosis.

ETHNOPHARMACOLOGICAL RELEVANCE: Psoralea corylifolia L. (P. corylifolia, also known as Cullen corylifolium (L.) Medik.) is a traditional medicinal her...

Alzheimer's disease risk prediction from clinical and social determinants of health: a machine learning cohort study in UK Biobank.

OBJECTIVES: Social determinants of health (SDOH) may improve Alzheimer's disease (AD) risk prediction by capturing upstream contextual risk beyond rou...

An intelligent MRI-based all-in-one diagnostic strategy for axillary lymph node status in breast cancer.

An integrated diagnostic strategy of preoperative identification of sentinel lymph node (SLN) metastasis, SLN metastatic burden, and non-SLN (NSLN) me...

Validation of aortic valve calcification quantification on contrast-enhanced computed tomography against ex vivo gravimetric analysis: comparison of fixed Hounsfield unit thresholds and deep learning segmentation.

BACKGROUND: Accurate quantification of aortic valve calcification (AVC) on contrast-enhanced computed tomography angiography (CTA) is pivotal for plan...

Development of an automated landmarking tool for the femur in dual-energy X-ray absorptiometry scans using contour-based image analysis.

Osteoporosis is a skeletal disease that significantly increases fracture risk and imposes a growing public health and economic burden. Notably, hip fr...

Tree-Based Machine Learning Model for Fluorescence Lifetime Prediction in Organic Compounds.

Fluorescence lifetime is a key photophysical property that reflects the excited-state decay dynamics of organic chromophores and is essential for appl...

Modeling antiretroviral therapy adherence among people living with HIV: a cross-sectional study at Pantang Hospital, Ghana.

BACKGROUND: Poor adherence to antiretroviral therapy (ART) continues to undermine HIV treatment outcomes in sub-Saharan Africa, including Ghana. OBJEC...

Sweat-based electrochemical wearable biosensors for sports performance and fatigue monitoring: from laboratory prototypes to field deployment.

Wearable biosensing technologies are advancing sports performance monitoring by enabling the continuous and real-time measurement of physiological and...