COVID-19

[Application of molecularly imprinted polymers-based sensors for determination of acute coronary syndrome biomarkers].

Cardiovascular diseases （CVDs） are among the leading cause of global morbidity and mortality. Due to their high prevalence and often asymptomatic progression， there is a pressing need for diagnostic tools that enable the early， accurate， and accessible detection of them. Acute coronary syndrome （ACS）， as a common and severe CVDs with high morbidity and mortality rates， has attracted considerable s...

Machine learning for detection of subclinical mastitis: A Bayesian approach incorporating diagnostic test properties.

The large amount of data collected through automatic milking systems (AMS) may be used for early detection of intramammary infections and become instrumental for monitoring udder health in dairy herds. Machine learning (ML) techniques can aid in improving diagnostic test properties of current indicators of subclinical mastitis (SCM). In this study, we present novel customized ML models for predict...

A Multimodal Fusion Model of Radiomics and Deep Learning Integrating the Tumor Microenvironment Accurately Predicts Pathological Complete Response in Breast Cancer.

BACKGROUND: Pathological complete response (pCR) to neoadjuvant chemotherapy (NAC) is a critical prognostic marker in breast cancer, yet its predictio...

Update on Non-Biological and RNA-Based Therapeutics in Chronic Inflammatory Diseases: Precision Medicine Through Small Molecules.

In the last decades, critical advancements in research technology and knowledge on disease mechanisms steered therapeutic approaches for chronic infla...

Development of an AI Image Recognition-Based Lateral Flow Immunochromatographic Test Strip for Higenamine Detection.

Higenamine (HM) is a naturally occurring benzylisoquinoline alkaloid found in plants and is classified as an S3 prohibited substance in the 2020 World...

Identification of glycosylation-related gene signatures associated with coronary artery disease via integrated transcriptomic and machine learning analyses.

BACKGROUND: On a global scale, coronary artery disease (CAD) continues to be one of the leading causes of morbidity and death. Glycosylation, a vital ...

Structure-Based Prediction of QT Prolongation Risk Using Graph Neural Networks: An Integrative Approach Combining In Vitro hERG Assays and Pharmacovigilance Data.

Drug-induced QT-interval prolongation, a non-specific biomarker of increased risk for Torsades de Pointes (TdP), is a major safety concern in drug dev...

Comparison of Artificial Intelligence Models for Automatic Segmentation of the Mandibular Canals and Branches.

OBJECTIVES: This study aimed to compare and improve the performance of three deep learning models, i.e., U-Net Transformer (UNETR), Swin UNETR, and 3D...

Artificial Intelligence Platform EnzySFC for Enzyme Screening and Functional Conversion: Completely Redirecting Nitrilase to Nitrile Hydratase Function.

Catalytic promiscuity provides fundamental insights into enzyme evolution. To address the multiobjective challenges in discovering and evolving promis...

A near-complete map of human cytosolic degrons and their relevance for disease.

Degrons are short protein segments that direct proteins for degradation via the ubiquitin-proteasome system, ensuring the removal of signaling protein...

Enhancing Anesthetic Depth Assessment via Unsupervised Machine Learning in Processed Electroencephalography Analysis: Novel Methodological Study.

BACKGROUND: General anesthesia comprises 3 essential components-hypnosis, analgesia, and immobility. Among these, maintaining an appropriate hypnotic ...

DiffMCG: A diffusion model with mask-conditioned guiding module for medical image classification.

Diffusion models have application potential in medical image classification tasks due to their effectiveness in eliminating unexpected noise and pertu...

Learning the Principles of T Cell Antigen Discernment.

T cells are central to the adaptive immune response, capable of detecting pathogenic antigens while ignoring healthy tissues with remarkable specifici...

Optimizing machine learning-based identification of sexual health influencers for HIV self-testing distribution among men who have sex with men in China: a secondary analysis of a quasi-experimental trial.

BACKGROUND: Secondary distribution of HIV self-testing can expand testing among men who have sex with men. A parent quasi-experimental trial found tha...

Integrated single-cell analyses of affinity-tested B cells enable the identification of a gene signature to predict antibody affinity.

Advancements in single-cell technologies and deep sequencing have expanded the B cell repertoire available for antibody discovery. However, selecting ...

An exploratory semantic analysis of age-related stereotypes in OpenAI's GPT 4o model.

BACKGROUND AND OBJECTIVES: Generative artificial intelligence, particularly large language models (LLMs), is increasingly used to navigate information...

Leveraging in-silico deep learning and computational analyses to predict the pathogenicity of ROBO4 variants of uncertain significance in aortic aneurysm and dissection patients.

Variants of uncertain significance (VUS) in genes implicated in thoracic aortic aneurysm (TAA) present clinical challenges due to ambiguous pathogenic...

AI-based analysis of label-free live cell imaging of T-cell mediated tumor killing assay enables competitive and robust hit calling.

For the discovery and optimization of personalized cancer treatments using immune cell therapeutics, such as T-cell receptor (TCR-T) therapy and bispe...

Machine learning-based COVID-19 prognostic models lag behind in reporting quality: findings from a TRIPOD/TRIPOD + AI systematic review.

BACKGROUND: Reporting of COVID-19 prognostic models frequently falls short of established standards. The TRIPOD checklist and its 2024 AI extension (T...

Deep Learning-Powered Scalable Cancer Organ Chip for Cancer Precision Medicine.

Functional precision oncology complements genomic approaches by directly testing treatment options on patient-derived models. However, existing platfo...