Preventive Care

Mapping vaccine names in clinical trials to vaccine ontology using cascaded fine-tuned domain-specific language models.

BACKGROUND: Vaccines have revolutionized public health by providing protection against infectious diseases. They stimulate the immune system and generate memory cells to defend against targeted diseases. Clinical trials evaluate vaccine performance, including dosage, administration routes, and potential side effects.

VacSol-ML(ESKAPE) Machine learning empowering vaccine antigen prediction for ESKAPE pathogens.

The ESKAPE family, comprising Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, and Enterobacter spp., poses a significant global threat due to their heightened virulence and extensive antibiotic resistance. These pathogens contribute largely to the prevalence of nosocomial or hospital-acquired infections, resulting in high morbidi...

AI support for colonoscopy quality control using CNN and transformer architectures.

BACKGROUND: Construct deep learning models for colonoscopy quality control using different architectures and explore their decision-making mechanisms.

Inhalation Toxicity Screening of Consumer Products Chemicals using OECD Test Guideline Data-based Machine Learning Models.

This study aimed to screen the inhalation toxicity of chemicals found in consumer products such as air fresheners, fragrances, and anti-fogging agents...

Cooperating Graph Neural Networks With Deep Reinforcement Learning for Vaccine Prioritization.

This study explores the vaccine prioritization strategy to reduce the overall burden of the pandemic when the supply is limited. Existing vaccine dist...

Multi-step framework for glaucoma diagnosis in retinal fundus images using deep learning.

Glaucoma is one of the most common causes of blindness in the world. Screening glaucoma from retinal fundus images based on deep learning is a common ...

Artificial Intelligence-Based Digital Biomarkers for Type 2 Diabetes: A Review.

Type 2 diabetes mellitus (T2DM), a complex metabolic disorder that burdens the health care system, requires early detection and treatment. Recent stri...

Lesion-Decoupling-Based Segmentation With Large-Scale Colon and Esophageal Datasets for Early Cancer Diagnosis.

Lesions of early cancers often show flat, small, and isochromatic characteristics in medical endoscopy images, which are difficult to be captured. By ...

Mass Spectrometric and Artificial Intelligence-Based Identification of the Secretome of Plasmodium falciparum Merozoites to Provide Novel Candidates for Vaccine Development Pipeline.

PURPOSE: Merozoites are the only extracellular form of blood stage parasites, making it a worthwhile target. Multiple invasins that are stored in the ...

Women's views on using artificial intelligence in breast cancer screening: A review and qualitative study to guide breast screening services.

As breast screening services move towards use of healthcare AI (HCAI) for screen reading, research on public views of HCAI can inform more person-cent...

Hybrid deep learning models for the screening of Diabetic Macular Edema in optical coherence tomography volumes.

Several studies published so far used highly selective image datasets from unclear sources to train computer vision models and that may lead to overes...

A deep learning framework for predicting endometrial cancer from cytopathologic images with different staining styles.

Endometrial cancer screening is crucial for clinical treatment. Currently, cytopathologists analyze cytopathology images is considered a popular scree...

Role of artificial intelligence in critical care nutrition support and research.

Nutrition plays a key role in the comprehensive care of critically ill patients. Determining optimal nutrition strategy, however, remains a subject of...

AGILE platform: a deep learning powered approach to accelerate LNP development for mRNA delivery.

Ionizable lipid nanoparticles (LNPs) are seeing widespread use in mRNA delivery, notably in SARS-CoV-2 mRNA vaccines. However, the expansion of mRNA t...

Endoscopic Artificial Intelligence for Image Analysis in Gastrointestinal Neoplasms.

BACKGROUND: Artificial intelligence (AI) using deep learning systems has recently been utilized in various medical fields. In the field of gastroenter...

Detection of atrial fibrillation using a nonlinear Lorenz Scattergram and deep learning in primary care.

BACKGROUND: Atrial fibrillation (AF) is highly correlated with heart failure, stroke and death. Screening increases AF detection and facilitates the e...

Integrated image-based deep learning and language models for primary diabetes care.

Primary diabetes care and diabetic retinopathy (DR) screening persist as major public health challenges due to a shortage of trained primary care phys...

An artificial intelligence-assisted system versus white light endoscopy alone for adenoma detection in individuals with Lynch syndrome (TIMELY): an international, multicentre, randomised controlled trial.

BACKGROUND: Computer-aided detection (CADe) systems for colonoscopy have been shown to increase small polyp detection during colonoscopy in the genera...

Leveraging artificial intelligence in vaccine development: A narrative review.

Vaccine development stands as a cornerstone of public health efforts, pivotal in curbing infectious diseases and reducing global morbidity and mortali...

Efficient multi-stage feedback attention for diverse lesion in cancer image segmentation.

In the domain of Computer-Aided Diagnosis (CAD) systems, the accurate identification of cancer lesions is paramount, given the life-threatening nature...