Menopause

Impact of land use on bus driver inattentiveness: Insight into crash risks.

OBJECTIVE: This study examines how roadside land-uses, namely commercial, residential, educational, and recreational establishments located on a typical Indian Highway, i.e., National Highway, influence the temporally distributed bus driver inattention, such as distraction, drowsiness, and falling asleep behaviors and their associated influence on the crash severity occurring on the entire study c...

Patient specific optimization and planning of vertebral augmentation in osteoporosis: Finite element and Artificial Intelligence approaches.

BACKGROUND: Osteoporotic Vertebral Compression Fractures (OVCFs) are responsible for significant disability, especially among individuals with low Bone Mineral Density (BMD). Although vertebral augmentation methods such as percutaneous vertebroplasty and kyphoplasty offer rapid pain relief and stability, the optimal combination of bone cement properties like volume, elasticity, and distribution re...

Clinical Machine Learning Model for Predicting Pathological Complete Response in Patients with Esophageal and Gastroesophageal Junction Adenocarcinoma After Trimodality Therapy.

BACKGROUND: Accurate prediction of pathological complete response (pCR) after preoperative chemoradiation therapy, followed by surgery (trimodality th...

Non-European migrants with schizophrenia spectrum disorders in Swiss forensic and general psychiatric care facilities - A comparative study using machine learning.

Personal history of migration poses an important risk factor for schizophrenia spectrum disorders (SSD), which are also associated with a higher rate ...

Deep-learning framework for osteoporosis screening on low-dose X-rays: Addressing image quality variability and cross-ethnic database Heterogeneity.

The AIXA Osteo model architecture (X1AI-Osteo) has undergone internal validation in Taiwan, demonstrating its capability to evaluate osteoporosis and ...

Interpretable depressive symptoms screening via statistical reasoning-augmented large language models using wearable and environmental data.

Early assessment of depressive symptoms is essential for scalable and personalized mental health care. We developed a hybrid clinical decision support...

Beyond saponins: An integrated mass spectrometry strategy for profiling, spatial mapping, and rapid authentication of non-saponin constituents in Panax species.

Non-saponin constituents of Panax species, including amino acids, sugars, and nucleosides, have attracted increasing attention due to their nutritiona...

Association of the Dietary Index for Gut Microbiota with site-specific Osteoporosis: Insights from machine learning applied to a national population.

BACKGROUND: The association between the Dietary Index for Gut Microbiota (DI-GM) and site-specific osteoporosis risk remains unclear. METHODS: This st...

Imaging without biology: limitations of CT-derived psoas muscle volume as a standalone diagnostic criterion for sarcopenia.

We comment on the study by Choi et al., which proposes CT-derived psoas muscle volume (PV) as a diagnostic indicator for sarcopenia. The study is well...

Physicochemical quality detection of wheat during hot air drying based on hyperspectral imaging combined with machine learning.

Hot air drying is widely used for wheat due to simple operation, but research on the intelligent regulation of the drying system based on product qual...

Lower pre-treatment TMS-evoked cortical reactivity and alpha-band oscillatory dynamics predict efficacy of primary motor cortex neuromodulation for chronic pain.

Repetitive transcranial magnetic stimulation (rTMS) to the primary motor cortex (M1) provides significant pain relief in ∼45% of chronic pain patients...

An algorithm to identify less invasive surfactant administration using a real-world database of preterm infants.

BACKGROUND: Surfactant replacement therapy is central to respiratory distress syndrome (RDS) management in preterm infants, which can be delivered usi...

Multi-site validation of an AI-based biomarker test for determining ER, PR, and HER2 status from H&E-stained breast cancer slides.

BACKGROUND: The assessment of estrogen/progesterone receptors (ER/PR) and human epidermal growth factor receptor 2 (HER2) is essential for managing br...

Integrated genomic profiling identifies predictive biomarkers for neoadjuvant therapy response in Chinese breast cancer patients.

Neoadjuvant therapy (NAT) has emerged as a standard treatment strategy for locally advanced breast cancer (BC), yet robust biomarkers for response pre...

Bone Magnetic Resonance Imaging: From Conventional Methods to AI-Driven Solutions.

With global population aging and increased life expectancy, bone diseases affect a substantial proportion of individuals worldwide, imposing a signifi...

A multiparameter model (OsteoSC-M3) for early detection and risk stratification of osteoporosis in women: a multicentre cohort study in China.

BACKGROUND: Osteoporosis is a major global health issue, but current early screening tools lack accuracy, and the gold-standard diagnostic method, dua...

Application of machine learning in osteoporosis screening: a narrative review.

Machine learning has the potential to address limitations of traditional osteoporosis screening through advanced data processing and pattern recogniti...

Neuroplasticity after Stroke: Adaptive and Maladaptive Mechanisms in Evidence-Based Rehabilitation.

BACKGROUND AND PURPOSE: Ischemic stroke remains a leading cause of long-term disability and persistent motor deficits. While neuroplasticity drives po...

Comment on "Assessing deep learning model performance in osteoporosis screening with lumbar spine radiographs".

Enabling ankle-brachial index prediction from doppler sounds using deep learning.

The ability to perform accurate point-of-care assessment of limb perfusion is critical for safe clinical decision-making. A formal ankle-brachial inde...