Menopause

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-minimum T-score from DEXA report, 2-maximum common bile duct (CBD) diameter from ultrasound report, and 3-maximum lung nodule size from CT report, and judging 1-presence of a highly hypermetabolic region on a PET report, 2-whether a patient is osteoporo...

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. Currently, no established, non-invasive method measures residual thymus in adults, its relationship with host immunity, or its influence on tumor immunosurveillance, cancer outcomes, and treatment-related toxicities. In a multi-institutional cohort o...

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 ...

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...

Identification of Risk Factors for Glaucoma Progression in Free-Text Clinical Notes using a Local Large Language Model

To evaluate the performance of a large language model (LLM) in identifying medication non-adherence, visit non-adherence, and family history of glauco...

Estrogen upregulates NF-κB and TNF signaling in B cells to cause sex and age differences in antibody responses to seasonal influenza vaccination

Sex differences in the humoral immune responses to the seasonal quadrivalent influenza vaccine (QIV) in young adults (YA; 18-49yo) or high dose QIV in...

The Hypothalamic Medial Preoptic Area-Paraventricular Nucleus Circuit Modulates Depressive-Like Behaviors in a Mouse Model of Postpartum Depression.

Estrogen fluctuations have been implicated in various mood disorders, including perimenopausal and postpartum depression (PPD), likely through complex...

Estimation of the air conditioning energy consumption of a classroom using machine learning in a tropical climate.

Air conditioning energy consumption in buildings represents a considerable percentage of total energy consumption, which underlines the importance of ...

Exploring the Mechanisms of Sanguinarine in the Treatment of Osteoporosis by Integrating Network Pharmacology Analysis and Deep Learning Technology.

BACKGROUND: Sanguinarine (SAN) has been reported to have antioxidant, antiinflammatory, and antimicrobial activities with potential for the treatment ...

DeepTransformer: Node Classification Research of a Deep Graph Network on an Osteoporosis Graph based on GraphTransformer.

BACKGROUND: Osteoporosis (OP) is one of the most common diseases in the elderly population. It is mostly treated with medication, but drug research an...

Diagnosis Osteoporosis Risk: Using Machine Learning Algorithms Among Fasa Adults Cohort Study (FACS).

INTRODUCTION: In Iran, the assessment of osteoporosis through tools like dual-energy X-ray absorptiometry poses significant challenges due to their hi...

An Empirical Evaluation of Large Language Models on Consumer Health Questions

This study evaluates the performance of several Large Language Models (LLMs) on MedRedQA, a dataset of consumer-based medical questions and answers ...

An Intrinsically Explainable Approach to Detecting Vertebral Compression Fractures in CT Scans via Neurosymbolic Modeling

Vertebral compression fractures (VCFs) are a common and potentially serious consequence of osteoporosis. Yet, they often remain undiagnosed. Opportu...

Improving Quantization-aware Training of Low-Precision Network via Block Replacement on Full-Precision Counterpart

Quantization-aware training (QAT) is a common paradigm for network quantization, in which the training phase incorporates the simulation of the low-...

Can We Get Rid of Handcrafted Feature Extractors? SparseViT: Nonsemantics-Centered, Parameter-Efficient Image Manipulation Localization through Spare-Coding Transformer

Non-semantic features or semantic-agnostic features, which are irrelevant to image context but sensitive to image manipulations, are recognized as e...