Preventive Care

Deep learning detection of diabetic retinopathy in Scotland's diabetic eye screening programme.

BACKGROUND/AIMS: Support vector machine-based automated grading (known as iGradingM) has been shown ...

A Machine Learning Framework for Screening Plasma Cell-Associated Feature Genes to Estimate Osteoporosis Risk and Treatment Vulnerability.

Osteoporosis, in which bones become fragile owing to low bone density and impaired bone mass, is a g...

Deep learning for osteoporosis screening using an anteroposterior hip radiograph image.

PURPOSE: Osteoporosis is a common bone disorder characterized by decreased bone mineral density (BMD...

Empowering standardization of cancer vaccines through ontology: enhanced modeling and data analysis.

BACKGROUND: The exploration of cancer vaccines has yielded a multitude of studies, resulting in a di...

A Paper-Based Multiplexed Serological Test to Monitor Immunity against SARS-COV-2 Using Machine Learning.

The rapid spread of SARS-CoV-2 caused the COVID-19 pandemic and accelerated vaccine development to p...

Machine learning screening of biomass precursors to prepare biomass carbon for organic wastewater purification: A review.

In the past decades, the amount of biomass waste has continuously increased in human living environm...

Machine Learning-Based Critical Congenital Heart Disease Screening Using Dual-Site Pulse Oximetry Measurements.

BACKGROUND: Oxygen saturation (Spo) screening has not led to earlier detection of critical congenita...

A versatile automated pipeline for quantifying virus infectivity by label-free light microscopy and artificial intelligence.

Virus infectivity is traditionally determined by endpoint titration in cell cultures, and requires c...

Title and abstract screening for literature reviews using large language models: an exploratory study in the biomedical domain.

BACKGROUND: Systematically screening published literature to determine the relevant publications to ...

Diabetic retinopathy screening through artificial intelligence algorithms: A systematic review.

Diabetic retinopathy (DR) poses a significant challenge in diabetes management, with its progression...

Systematic Review and Meta-Analysis of Prehospital Machine Learning Scores as Screening Tools for Early Detection of Large Vessel Occlusion in Patients With Suspected Stroke.

BACKGROUND: Enhanced detection of large vessel occlusion (LVO) through machine learning (ML) for acu...

Utilizing machine learning for early screening of thyroid nodules: a dual-center cross-sectional study in China.

BACKGROUND: Thyroid nodules, increasingly prevalent globally, pose a risk of malignant transformatio...

UPLC-Q-TOF-MS/MS combined with machine learning methods for screening quality indicators of Hypericum perforatum L.

Hypericum perforatum L. (HPL), also known as St. John's wort, is one of the extensively researched d...

A Machine Learning Approach to Identify Key Residues Involved in Protein-Protein Interactions Exemplified with SARS-CoV-2 Variants.

Human infection with the coronavirus disease 2019 (COVID-19) is mediated by the binding of the spike...

Point-of-care AI-enhanced novice echocardiography for screening heart failure (PANES-HF).

The increasing prevalence of heart failure (HF) in ageing populations drives demand for echocardiogr...

Beyond the : A Breakthrough in the Use of Artificial Intelligence for Mammography in Screening for Breast Cancer.

Artificial Intelligence in Colorectal Cancer: From Patient Screening over Tailoring Treatment Decisions to Identification of Novel Biomarkers.

BACKGROUND: Artificial intelligence (AI) is increasingly entering and transforming not only medical ...

Support Vector Machine-Based Formula for Detecting Suspected α Thalassemia Carriers: A Path toward Universal Screening.

The blood counts of α thalassemia carriers (α-thal) are similar to those of β thalassemia carriers, ...

Utilization of machine learning for dengue case screening.

Dengue causes approximately 10.000 deaths and 100 million symptomatic infections annually worldwide,...

Artificial intelligence-driven computer aided diagnosis system provides similar diagnosis value compared with doctors' evaluation in lung cancer screening.

OBJECTIVE: To evaluate the consistency between doctors and artificial intelligence (AI) software in ...

Prediction model of preeclampsia using machine learning based methods: a population based cohort study in China.

INTRODUCTION: Preeclampsia is a disease with an unknown pathogenesis and is one of the leading cause...