Menopause

Longitudinal development of sex differences in the limbic system is associated with age, puberty and mental health

Sex differences in mental health become more evident across adolescence, with a two-fold increase of prevalence of mood disorders in females compared to males. The brain underpinnings remain understudied. Here, we investigated the role of age, puberty and mental health in determining the longitudinal development of sex differences in brain structure. We captured sex differences in limbic and non-l...

Objective Assessment of Microperimetry Exam Using EEG Signals

To test the hypothesis that deep learning can decode single-trial cortical responses from electroencephalography (EEG) to individual, long-duration microperimetry (MP) stimuli, thereby providing a basis for an objective measure of visual pathway integrity. We also investigated whether occipital EEG signals could automatically register microperimetry stimuli, replacing the patient’s manual button p...

Open-source DeepSeek-R1 Outperforms Proprietary Non-Reasoning Large Language Models With and Without Retrieval-Augmented Generation

To compare reasoning large language models (LLMs) vs. non-reasoning LLMs and open-source DeepSeek models vs. proprietary LLMs in answering ophthalmolo...

Artificial Intelligence in Reminiscence Therapy for Older Adults: A Systematic Review Protocol

The global aging population faces increasing challenges related to cognitive decline, social isolation, and psychological well-being. Reminiscence the...

Breath-Based Monitoring of High Cholesterol State and Statin Therapy

Monitoring the effectiveness of statin therapy in patients with dyslipidemia is essential for ensuring optimal treatment outcomes. The current standar...

Using deep learning to improve genetic studies of osteoporosis

To evaluate how recent advances in deep learning can improve the construction of quantitative phenotypes for genome-wide association studies (GWAS), w...

Non-Traditional Lipid Ratios Predict Cardiovascular-Kidney-Metabolic Syndrome: Insights from Machine Learning Model Using NHANES Data

Cardiovascular-kidney-metabolic (CKM) syndrome is a newly defined multisystem disease continuum characterized by the coexistence of metabolic dysfunct...

Glomerular Segmentation, Classification, and Pathomic Feature-based Prediction of Clinical Outcomes in Minimal Change Disease and Focal Segmental Glomerulosclerosis

Conventional assessment of Focal Segmental Glomerulosclerosis and Minimal Change Disease focuses on the presence/extent of segmental (SS) and global (...

Development of Self-Assessment Tools for Osteoporosis among Postmenopausal Vietnamese Women: A Machine Learning Approach

Osteoporosis is a major health concern in Vietnam due to a rise in aging rates. However, cost-effective early screening tools tailored to the Vietname...

Large language models in radiologic numerical tasks: A thorough evaluation and error analysis

To investigate the performance of LLMs in radiology numerical tasks and perform a comprehensive error analysis. We defined six tasks: extracting 1-min...

Thymus Composition, Disease Control, and Toxicity in Locally Advanced Lung Cancer

Thymic involution, characterized by adipose replacement of functional thymic tissue, is a broadly recognized feature of age-related immunosenescence. ...

DNA-Based Deep Learning and Association Studies for Drug Response Prediction in Leiomyosarcoma

Leiomyosarcoma (LMS) is a rare and aggressive soft tissue sarcoma with limited treatment options and poor prognosis. Standard therapies, including dox...

Leveraging simulation to provide a practical framework for assessing the novel scope of risk of LLMs in healthcare

Large language models (LLMs) are rapidly entering clinical care, yet their definitionally probabilistic outputs have delivered a variety of grossly un...

The Promise and Peril of Large Language Models in Digital Health: GPT-4 Personalizes Cardiovascular Patient Education but Amplifies Gender Biases

Gender-neutral patient education materials often overlook critical sex-based differences in cardiovascular disease (CVD). Large Language Models (LLMs)...

Accurate, Race-Free LDL-C Estimation in Non-Fasting Settings: A Machine-Learning Study in 3,477 Adults

Traditional LDL-C testing barriers—mandatory 9–12 hour fasting and inperson visits—disproportionately limit access for rural populations (60% of US co...

Prognosis After First-Trimester Threatened Miscarriage: A Systematic Review, Prognostic Accuracy Meta-Analysis, And Prediction Modelling Review

Threatened miscarriage represents one of the most prevalent obstetric emergencies globally. Nevertheless, women experiencing first-trimester bleeding ...

Performance of reasoning large language models on nephrology multiple-choice questions

Performance of large language models in medicine is improving, yet it remains unclear how the advantage of reasoning models depends on task characteri...

PATHOS: Predicting Variant Pathogenicity by Combining Protein Language Models and Biological Features

Predicting the pathogenic impact of missense variants is essential for understanding and diagnosing genetic diseases. These approaches have undergone ...

Data Extraction from Oncology Imaging Reports by Large Language Models: A Comparative Accuracy Study

Manual data extraction from clinical text is resource intensive. Locally hosted large language models (LLMs) may offer a privacy-preserving solution, ...

Artificial intelligence for aortic valve calcium score quantification by echocardiography

Aortic valve calcification (AVC), as measured by gold-standard computed tomography (CT) Agatston score, provides an anatomic assessment of aortic sten...