Osteoporosis

Early Identification of Mobility Limitations in Community-Dwelling Middle-Aged and Older Adults: Development of a Prediction Model Based on a Prospective Cohort.

BACKGROUND: With the aging of the global population, preventing the onset of mobility limitations is considered a worldwide public health priority. OBJECTIVE: This study aimed to develop a predictive model for incident early mobility limitations (EMLs) in late middle-aged and older adults, based on a simple functional test and modifiable lifestyle factors to facilitate a home-based self-assessment...

Machine learning prediction for menopause women with low bone mass: a multicenter and retrospective study.

Early diagnosis of postmenopausal osteoporosis provides an opportunity to detect and prevent fractures. This study uses machine learning (ML) techniques to enhance the predictive ability for low bone mass (LBM) risk. A retrospective cross-sectional study was performed, including 3,738 menopausal women from a hospital (the internal validation dataset) and 1,008 menopausal women from the community (...

Development of AI-assisted 3D-printed degradable hydrogel microneedles for transdermal delivery of progesterone-loaded solid lipid nanoparticles: a novel approach to slowing Alzheimer's disease progression.

Progesterone (PG) is used to slow the progression of neurodegenerative diseases, particularly Alzheimer's disease (AD) in postmenopausal women. Howeve...

Opportunistic screening for osteoporosis using chest X-rays and deep learning: A systematic review and meta-analysis.

PURPOSE: To evaluate the diagnostic performance of deep learning (DL) algorithms applied to chest radiographs (CXR) for detecting osteoporosis and ass...

Mitochondrial Gene Signature Reveals Novel Diagnostic Biomarkers for Autism Spectrum Disorder.

Autism Spectrum Disorder (ASD) pathogenesis remains unclear, with mitochondrial dysfunction implicated as a key contributor. Reliable mitochondrial-re...

Pathophysiological mechanisms of High-Pressure Nervous Syndrome: A Comprehensive review.

High-Pressure Nervous Syndrome (HPNS) refers to a series of neurological disturbances that occur during exposure to high hydrostatic pressure, charact...

Genetics of bipolar disorder: Translating discoveries to biological insights and clinical decision support.

Bipolar disorder (BD) is a clinically heterogenous mental disorder with a diversity in clinical trajectories and treatment response. Twin studies have...

An intelligent auxiliary diagnostic system for early osteoporosis screening using stacking ensemble learning.

Artificial intelligence denoising in cardiac photon-counting CT: mitigating BMI-related noise degradation while maintaining clinical interchangeability.

OBJECTIVES: To evaluate whether an artificial intelligence-based denoising (AID) algorithm can effectively attenuate body mass index (BMI)-related noi...

Studying the Influence of pH of the Water Quality of King Talal Dam using Data Mining Technique.

This study investigates the effect of pH on the water quality of King Talal Dam (KTD) in Jordan, utilizing data mining analysis. With treated wastewat...

Expert Evaluation of the Perceived Accuracy, Relevance, and Safety of Large Language Model-Generated Patient Information in Geriatrics: Cross-Condition Study.

BACKGROUND: Large language models (LLMs) are increasingly used to generate patient-oriented medical information. In geriatrics, such information must ...

Identification of potential biomarkers for osteoporosis and chronic kidney disease through bioinformatics and machine learning algorithm.

OBJECTIVE: The purpose of this study is to identify hub genes associated with both osteoporosis (OP) and chronic kidney disease (CKD) through bioinfor...

The Use of Statistical Shape and Appearance Modelling for Predicting Osteoporotic Fracture Risk.

PURPOSE OF REVIEW: Osteoporotic fractures remain a major cause of morbidity and mortality worldwide. Current clinical assessment metrics (e.g., bone m...

Deciphering the predictors of endometrial nonbenign lesions in asymptomatic postmenopausal women via explainable machine learning.

OBJECTIVES: Timely identification of endometrial nonbenign lesions led to improved outcomes, but there was a lack of effective predictive models for a...

T3SS effector and regulator discovery by predicting interacting partners of T3SS chaperones in Pseudomonas aeruginosa.

Pseudomonas aeruginosa is a prominent opportunistic pathogen whose virulence is closely linked to its Type III Secretion System (T3SS), a specialized ...

Single-neuron network topology governs neural computation and learning in primate cortex.

Neural networks underlie complex brain information processing, yet the role of their single-neuron topology in governing computation and behavior rema...

Assessing osteosarcopenia using automated multi-structure-segmentation and Hounsfield unit-based analysis of lumbar muscles and vertebral bodies on computed tomography.

Sarcopenia and osteoporosis are prevalent age-related conditions that substantially increase the risk of falls, fractures, and functional decline. Thi...

Beyond coronary artery calcium score: can lipoprotein(a) and artificial intelligence-coronary computed tomography angiography unmask 'invisible' residual cardiovascular risk?

Rotenone impairs osteoclastogenesis by inhibiting cell migration: insights from machine learning.

PURPOSE: The migration and fusion of osteoclast precursors (OCPs) are critical steps in osteoclastogenesis and require substantial energy. Although ox...

Response to comment on "Assessing deep learning model performance in osteoporosis screening with lumbar spine radiographs".