Menopause

Data fusion of near-infrared and Raman spectroscopy: An innovative tool for non-destructive prediction of the TVB-N content of salmon samples.

Total volatile basic nitrogen (TVB-N) serves as a crucial indicator for evaluating the freshness of ...

A non-invasive preoperative prediction model for predicting axillary lymph node metastasis in breast cancer based on a machine learning approach: combining ultrasonographic parameters and breast gamma specific imaging features.

BACKGROUND: The most common route of breast cancer metastasis is through the mammary lymphatic netwo...

An Artificial Neural Network Predicts Gender Differences of Motor and Non-Motor Symptoms of Patients with Advanced Parkinson's Disease under Levodopa-Carbidopa Intestinal Gel.

: Currently, no tool exists to predict clinical outcomes in patients with advanced Parkinson's disea...

Lack of evidence for predictive utility from resting state fMRI data for individual exposure-based cognitive behavioral therapy outcomes: A machine learning study in two large multi-site samples in anxiety disorders.

Data-based predictions of individual Cognitive Behavioral Therapy (CBT) treatment response are a fun...

Federated learning using model projection for multi-center disease diagnosis with non-IID data.

Multi-center disease diagnosis aims to build a global model for all involved medical centers. Due to...

nBEST: Deep-learning-based non-human primates Brain Extraction and Segmentation Toolbox across ages, sites and species.

Accurate processing and analysis of non-human primate (NHP) brain magnetic resonance imaging (MRI) s...

Machine-learning models for diagnosis of rotator cuff tears in osteoporosis patients based on anteroposterior X-rays of the shoulder joint.

OBJECTIVE: This study aims to diagnose Rotator Cuff Tears (RCT) and classify the severity of RCT in ...

Utilizing machine learning to predict post-treatment outcomes in chronic non-specific neck pain patients undergoing cervical extension traction.

This study explored the application of machine learning in predicting post-treatment outcomes for ch...

Assessment of image quality and impact of deep learning-based software in non-contrast head CT scans.

In this retrospective study, we aimed to assess the objective and subjective image quality of differ...

Preoperatively predicting survival outcome for clinical stage IA pure-solid non-small cell lung cancer by radiomics-based machine learning.

OBJECTIVE: Clinical stage IA non-small cell lung cancer (NSCLC) showing a pure-solid appearance on c...

Enhancing clinical utility: deep learning-based embryo scoring model for non-invasive aneuploidy prediction.

BACKGROUND: The best method for selecting embryos ploidy is preimplantation genetic testing for aneu...

Integration of bioinformatics and machine learning approaches for the validation of pyrimidine metabolism-related genes and their implications in immunotherapy for osteoporosis.

BACKGROUND: Osteoporosis (OP), the "silent epidemic" of our century, poses a significant challenge t...

Smartphone based wearable sweat glucose sensing device correlated with machine learning for real-time diabetes screening.

BACKGROUND: Diabetes is a significant health threat, with its prevalence and burden increasing world...

Points of interest linear attention network for real-time non-rigid liver volume to surface registration.

BACKGROUND: In laparoscopic liver surgery, accurately predicting the displacement of key intrahepati...

Prevalence of non-communicable chronic diseases in rural India amongst peri- and post-menopausal women: Can artificial intelligence help in early identification?

AIMS: To identify peri- and post-menopausal women at risk of non-communicable diseases in rural Indi...

Impact of an artificial intelligence based model to predict non-transplantable recurrence among patients with hepatocellular carcinoma.

OBJECTIVE: We sought to develop Artificial Intelligence (AI) based models to predict non-transplanta...

Possible role of artificial intelligence in diagnosis of cases with non-specific signs and symptoms of dengue: A comment.

Large-scale 3D non-Cartesian coronary MRI reconstruction using distributed memory-efficient physics-guided deep learning with limited training data.

OBJECT: To enable high-quality physics-guided deep learning (PG-DL) reconstruction of large-scale 3D...

Experimental and Machine-Learning-Assisted Design of Pharmaceutically Acceptable Deep Eutectic Solvents for the Solubility Improvement of Non-Selective COX Inhibitors Ibuprofen and Ketoprofen.

Deep eutectic solvents (DESs) are commonly used in pharmaceutical applications as excellent solubili...

A non-invasive method to determine core temperature for cats and dogs using surface temperatures based on machine learning.

BACKGROUND: Rectal temperature (RT) is an important index of core temperature, which has guiding sig...

Deep-learning survival analysis for patients with calcific aortic valve disease undergoing valve replacement.

Calcification of the aortic valve (CAVDS) is a major cause of aortic stenosis (AS) leading to loss o...