HRT

Improving predicted risk of recurrence using molecular profiling in papillary thyroid cancer.

Molecular testing can refine the prediction of cancer recurrence. We sought to compare patterns of gene expression in patients with and without recurrence of well-differentiated thyroid cancer to identify pathways associated with recurrence and develop a predictive model based on gene expression. RNA was extracted and sequenced from archival tumor samples of patients well-differentiated thyroid ca...

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

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...

Evaluation of the accuracy and readability of large language model responses on menopause and hormone therapy.

OBJECTIVE: Generative artificial intelligence is rapidly evolving and is now being explored in health care to support patient and clinician education....

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...

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...

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".

Multimodal data analysis reveals asynchronous aging dynamics across female reproductive organs.

Female reproductive aging has systemic health implications, yet tissue-level dynamics remain poorly understood. Here we integrate deep learning analys...

Diagnosis of Acromegaly.

The clinical presentation of acromegaly reflects systemic effects of chronic GH and IGF-I excess. Diagnostic delay frequently ranges from 6 to 10 year...

Integrative gene ontology-driven analysis of the eutopic endometrium reveals key dysregulated functionomes and pathways in endometriosis.

BACKGROUND: Endometriosis is a chronic estrogen-dependent inflammatory disorder associated with pelvic pain, infertility, and an increased risk of end...

Development of machine learning models for predicting early pregnancy outcomes based on β-hCG, progesterone, and estradiol.

OBJECTIVE: This study aims to develop a machine learning model for predicting early pregnancy outcomes by combining baseline levels and dynamic change...

Game of clones: decipher lineage plasticity in hormone-driven cancers.

Hormone-dependent cancers such as prostate, breast, and endometrial carcinomas rely on nuclear hormone receptors to sustain lineage identity and growt...

SuperLearner approach for predicting imminent risk of fracture in older Chinese patients with newly diagnosed osteoporosis based on their routine blood test markers.

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 Bon...

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 ...

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...