Menopause

In Silico tool for predicting, designing and scanning IL-2 inducing peptides.

Interleukin-2 (IL-2) based immunotherapy has been approved for treating certain types of cancer, as ...

A non-anatomical graph structure for boundary detection in continuous sign language.

Recently, the challenge of the boundary detection of isolated signs in a continuous sign video has b...

Non-invasive liver fibrosis screening on CT images using radiomics.

PURPOSE: To develop a radiomics machine learning model for detecting liver fibrosis on CT images of ...

Predictive modeling for step II therapy response in periodontitis - model development and validation.

Steps I and II periodontal therapy is the first-line treatment for periodontal disease, but has vary...

Integrating vision transformer-based deep learning model with kernel extreme learning machine for non-invasive diagnosis of neonatal jaundice using biomedical images.

Birth complications, particularly jaundice, are one of the leading causes of adolescent death and di...

Deep Learning for Osteoporosis Diagnosis Using Magnetic Resonance Images of Lumbar Vertebrae.

This work uses T1, STIR, and T2 MRI sequences of the lumbar vertebrae and BMD measurements to identi...

Machine learning survival models for Non-alcoholic fatty liver disease based on a health checkup cohort.

OBJECTIVES: This study aimed to develop an accurate prediction model for the risk of Non-alcoholic f...

Characterizing individual and methodological risk factors for survey non-completion using machine learning: findings from the U.S. Millennium Cohort Study.

BACKGROUND: Missing survey data can threaten the validity and generalizability of findings from long...

A Novel Machine Learning Model for Predicting Natural Conception Using Non-Laboratory-Based Data.

This study aimed to predict the likelihood of natural conception among couples by using a machine le...

A Scoping Review on AI-Supported Interventions for Non-Pharmacological Management of Chronic Rheumatic Diseases.

This review summarizes AI-supported non-pharmacological interventions for adults with chronic rheuma...

Deep learning algorithm for identifying osteopenia/osteoporosis using cervical radiography.

Due to symptomatic gait imbalance and a high incidence of falls, patients with cervical disease-incl...

Incidental Finding of Coronary and Non-Coronary Artery Calcium: What Do Clinicians Need To Know?

PURPOSE OF REVIEW: This review summarizes the role of incidentally and non-incidentally discovered c...

A novel dual embedding few-shot learning approach for classifying bone loss using orthopantomogram radiographic notes.

BACKGROUND: Orthopantomograms (OPGs) are essential diagnostic tools in dental and maxillofacial care...

Non-invasive identification of TKI-resistant NSCLC: a multi-model AI approach for predicting EGFR/TP53 co-mutations.

OBJECTIVES: To investigate the value of multi-model based on preoperative CT scans in predicting EGF...

Predicting antiretroviral therapy adherence status of adult HIV-positive patients using machine-learning Northwest, Ethiopia, 2025.

BACKGROUND: Adherence with Anti-Retroviral Therapy (ART) reduces viral load, as well as HIV-related ...

Enhanced melanoma and non-melanoma skin cancer classification using a hybrid LSTM-CNN model.

Melanoma is the most dangerous type of skin cancer. Although it accounts for only about 1% of all sk...

PREACT-digital: study protocol for a longitudinal, observational multicentre study on digital phenotypes of non-response to cognitive behavioural therapy for internalising disorders.

INTRODUCTION: Cognitive behavioural therapy (CBT) serves as a first-line treatment for internalising...

Value-Based Care in Orthopaedic Surgery: Outcomes, Costing, and Policy Updates.

➢ Strategic action following the measurement of outcomes in the context of cost allows for the reall...

Early prediction of non-invasive ventilation outcome using the TabPFN machine learning model: a multi-centre validation study.

Utilizing Immuno-Oncology registry data for enhanced non-small cell lung cancer treatment predictions.

OBJECTIVES: We aim to leverage more comprehensive phenotypic and genotypic clinical data to enhance ...

CRISPR/Cas-Based Biosensing Strategies for Non-Nucleic Acid Contaminants in Food Safety: Status, Challenges, and Perspectives.

Non-nucleic acid targets (non-NATs), such as heavy metals, toxins, and pesticide residues, pose crit...