Menopause

Predicting total knee replacement in knee osteoarthritis using a machine learning-guided approach in patients of the Osteoarthritis Initiative (OAI).

OBJECTIVE: To develop a pragmatic model to predict total knee replacement (TKR) in knee osteoarthrit...

Artificial Intelligence-based analysis of pre-eclampsia gene expression profiles for identification of novel potential pre-eclampsia diagnostic biomarkers.

Preeclampsia (PE) is a multifactorial and heterogeneous hypertensive disorder of pregnancy that pose...

Association of epicardial adipose tissue with markers of cardiac remodelling and clinical outcomes in asymptomatic aortic stenosis.

BACKGROUND: Previous studies have suggested an adverse role of epicardial adipose tissue (EAT) in ao...

High-Resolution MRI Using Artificial Intelligence-Assisted Acceleration and Radial Dynamic Contrast Enhancement for Improved Detection of Pituitary Microadenomas in Cushing's Disease.

BACKGROUND AND PURPOSE: Accurate detection of pituitary microadenomas is critical for the diagnosis ...

Profiling reasons for non-attendance in psychological assessments in adolescent suicide at-risk group using natural language processing.

BACKGROUND: Non-attendance at follow-up psychological evaluations is a major barrier to care for ado...

Opportunistic osteoporosis screening using CT-based Hounsfield units: a machine learning approach for preoperative spine surgery planning.

Attitudes toward AI in health- and non-health-related contexts: Context matters, not mood or perceived social support.

As artificial intelligence (AI) systems increasingly permeate healthcare and daily life, understandi...

Wearable electrochemical biosensors for non-invasive sport doping control: sweat and saliva as dual biofluid platforms.

The integrity of competitive athletics is increasingly compromised by sophisticated pharmacologies, ...

Open-Source Machine Learning Computed Tomography Scan Segmentation for Spine Osteoporosis Diagnostics.

BACKGROUND AND OBJECTIVES: Dual-energy x-ray absorptiometry (DXA) is the standard for assessing bone...

Auto-LSN: fully automated liver surface nodularity quantification in CT based on deep learning for the evaluation of advanced chronic liver disease.

OBJECTIVES: Liver surface nodularity (LSN) is a recognized non-invasive biomarker of cirrhosis. This...

Evaluation of deliverable dose-mimicking automated volumetric arc radiation therapy planning for stage III non-small cell lung cancer patients: comparison with a commercial DVH-predicted automated planning system.

This study aimed to evaluate the clinical validity of a dose-mimicking automated planning for volume...

Ethical Risks and Structural Implications of AI-Mediated Medical Interpreting.

Artificial intelligence (AI) is increasingly used to support medical interpreting and public health ...

Impacts of delayed influenza vaccination on clinical outcomes in ICU-admitted patients with influenza: A retrospective cohort study.

BACKGROUND: Influenza vaccination is an effective measure for reducing the risk of severe influenza ...

Association of urinary heavy metals with osteoporosis in US adults using interpretable machine learning.

BACKGROUND: Exposure to heavy metals in the environment has always been the focus of public concern....

Machine learning-enabled meta-analysis reveals the effect of microplastics on nitrogen removal performance in constructed wetlands and its potential mechanisms.

Constructed wetlands (CWs) are an effective wastewater treatment system and an important sink for mi...

Fracture risk scores using output from an opportunistic screen of low bone density from conventional X-ray.

Fracture risk is commonly assessed by FRAX, a tool that estimates 10-yr risk for major osteoporotic ...

Near-infrared spectroscopy and machine-learning evaluation of PVA/β-TCP biomaterial composites.

A composite of polyvinyl alcohol (PVA) and beta-tricalcium phosphate (β-TCP) was synthesized as a bi...

Circulating tumor DNA dynamics predict pathological response and guide therapy personalization in the neoadjuvant setting.

Neoadjuvant therapy is a cornerstone of modern oncology, yet its efficacy is traditionally assessed ...

Osteoporosis prediction using lumbar CT Hounsfield units: comparative performance and clinical implications of seven machine learning models.

PURPOSE: This study aimed to evaluate the utility of L1-L4 average Hounsfield Unit (HU) values from ...

Lipid monitoring using non-invasive measurement technologies and machine learning: a systematic review.

BACKGROUND: Cardiovascular diseases (CVD) are the leading cause of death among women, with risk incr...

Padé Neurons for Efficient Neural Models.

Neural networks commonly employ the McCulloch-Pitts neuron model, which is a linear model followed b...