Menopause

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 glaucoma (FHoG) in clinical notes from the electronic health record (EHR). We extracted clinical notes of 1,250 glaucoma-related encounters between 2014 and 2024 and structured EHR family history field data from the Bascom Palmer Ophthalmic Repository, wit...

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 old adults (OA; 75+yo) were analyzed to evaluate how age-related changes in steroids impact sex differences in B cell responses. Among YAs, females had greater H3N2, but not H1N1, neutralizing antibody titers and greater proportions of hemagglutinin...

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...

Comparison of Different Machine Learning Methodologies for Predicting the Non-Specific Treatment Response in Placebo Controlled Major Depressive Disorder Clinical Trials.

Placebo effect represents a serious confounder for the assessment of treatment effect to the extent that it has become increasingly difficult to devel...

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 ...

FedVCK: Non-IID Robust and Communication-Efficient Federated Learning via Valuable Condensed Knowledge for Medical Image Analysis

Federated learning has become a promising solution for collaboration among medical institutions. However, data owned by each institution would be hi...

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...

Computer-Aided Osteoporosis Diagnosis Using Transfer Learning with Enhanced Features from Stacked Deep Learning Modules

Knee osteoporosis weakens the bone tissue in the knee joint, increasing fracture risk. Early detection through X-ray images enables timely intervent...

The Helicobacter pylori AI-Clinician: Harnessing Artificial Intelligence to Personalize H. pylori Treatment Recommendations

Helicobacter pylori (H. pylori) is the most common carcinogenic pathogen worldwide. Infecting roughly 1 in 2 individuals globally, it is the leading...

Osteoporosis Prediction from Hand X-ray Images Using Segmentation-for-Classification and Self-Supervised Learning

Osteoporosis is a widespread and chronic metabolic bone disease that often remains undiagnosed and untreated due to limited access to bone mineral d...

AI-Driven Non-Invasive Detection and Staging of Steatosis in Fatty Liver Disease Using a Novel Cascade Model and Information Fusion Techniques

Non-alcoholic fatty liver disease (NAFLD) is one of the most widespread liver disorders on a global scale, posing a significant threat of progressin...

BinSparX: Sparsified Binary Neural Networks for Reduced Hardware Non-Idealities in Xbar Arrays

Compute-in-memory (CiM)-based binary neural network (CiM-BNN) accelerators marry the benefits of CiM and ultra-low precision quantization, making th...

Scalable Image Tokenization with Index Backpropagation Quantization

Existing vector quantization (VQ) methods struggle with scalability, largely attributed to the instability of the codebook that undergoes partial up...

Concept Replacer: Replacing Sensitive Concepts in Diffusion Models via Precision Localization

As large-scale diffusion models continue to advance, they excel at producing high-quality images but often generate unwanted content, such as sexual...