COVID-19

Deep learning for automated instance segmentation of residual roots in panoramic radiographs using mask R-CNN: A retrospective diagnostic accuracy study.

BACKGROUND: This study aimed to evaluate the efficacy of Mask regions with convolutional neural network (R-CNN) for the automated detection and segmentation of residual dental roots in panoramic radiographs and to compare its diagnostic performance against the semantic segmentation benchmark, U-shaped network (U-Net). METHODS: A retrospective dataset comprising 224 patients with 505 annotated resi...

Smart wearable biosensors: a transformative synergy between diagnosis and treatment of disease.

Smart wearable biosensors represent a significant paradigm shift from one-time sample analysis to real-time biochemical monitoring at the body interface. Besides the flexible design of the device or wireless readout, their clinical utility will also require the reliability of the entire sensing pathway under real physiological conditions. This pathway involves biofluid access to clinical interpret...

Characterization and Validation of EHR Computable Phenotypes for Long COVID Using Patient-Reported Symptoms: Insights from the Nationwide RECOVER Program.

OBJECTIVE: Long COVID (LC) remains poorly understood, and there is a critical need for advanced computational tools to better identify and characteriz...

Interpretable dynamic quantitative vascular morphometry features using SHAP for anti-angiogenic therapy response prediction.

Anti-angiogenic therapy benefits vary, with response rates of 40 to 70%, highlighting the need for early biomarkers to identify responders. We develop...

Persona-Driven Data Augmentation for Disease Name Recognition Across Rare and General Disease Corpora: Comparative Evaluation Study.

BACKGROUND: Medical information extraction requires automatically identifying disease names and related terms in text. This task, known as named entit...

Epitope-Specific IgE Profiles are Predictive of Desensitization and Remission in the IMPACT Trial.

BACKGROUND: Results from the IMPACT trial suggest that initiation of peanut oral immunotherapy (pnOIT) before age 4 years can increase chances of achi...

The underlying mechanisms of tDCS-Based cognitive enhancement in unpredictable task switching: A machine learning-based approach for EEG signal analysis.

Transcranial direct current stimulation (tDCS) enhances cognitive abilities yet has highly inconsistent outcomes, highlighting the need to clarify its...

Single-cell analysis of the epigenome and 3D chromatin architecture in the human retina.

Most genetic risk variants linked to ocular diseases are nonprotein coding and presumably contribute to disease through dysregulation of gene expressi...

Integrative multi-omics reveals NQO1-mediated airway epithelial injury as a key mechanism of bisphenol A-induced COPD.

Bisphenol A (BPA) is a ubiquitous environmental pollutant, but its relationship with chronic obstructive pulmonary disease (COPD) and the underlying t...

Multi-omics and genetic prioritization identify candidate molecular links between micro- and nanoplastics-associated signatures and chronic kidney disease.

Micro- and nanoplastics (MNPs) have been detected in human renal and urinary tissues and are increasingly recognized as potential environmental contri...

Battling the Bots and Defending Against Fraudulent Responses in an International Community-Engaged Web-Based Survey With People Living With Long COVID: Methodological Study.

BACKGROUND: Web-based surveys involving self-reported questionnaires are vulnerable to fraudulent responses. Advancements in artificial intelligence a...

Personalized cancer vaccines: bridging immune-oncology and precision medicine for advanced therapeutics.

Despite advancements in therapeutic cancer vaccines, clinical translation has been hindered by limited efficacy, with Sipuleucel-T remaining the only ...

VN1K is a pangenome-informed multi-omics and phenomics resource for the Vietnamese population.

The population of Vietnam remains underrepresented in global genomic databases. Here, we present VN1K, a resource of multi-omics and phenotypic inform...

Integrating multi-index remote sensing and machine learning for mangrove dynamics assessment using sentinel-2 imagery.

Mangrove ecosystems in the Indus Delta provide critical coastal protection, carbon storage, and biodiversity support but remain vulnerable to environm...

Classification models for KCNQ1 variants distinguish functional and trafficking effects to enhance pathogenicity interpretation.

Missense variants in the potassium channel KCNQ1 underlie most cases of congenital long QT syndrome (LQTS), one of the most common genetic arrhythmias...

Recent Advances in Immunotherapy for Breast Cancer: An Updated Review.

Immunotherapy has revolutionized the treatment landscape of breast cancer, particularly for triple-negative breast cancer (TNBC), yet primary and acqu...

Harnessing AI and social media to understand real-world patient experiences in SLE.

OBJECTIVE: To apply large language models (LLMs) to Reddit posts referencing SLE to identify patient-expressed unmet medical needs, symptom experience...

Artificial intelligence perceives marginal gains from MHC class I haplotype data in antigen presentation predictions.

Artificial Intelligence offers valuable tools for scientific discovery, but when used improperly, it can cause blunders. In this paper, we report find...

Benchmarking deep learning pipelines for surgical instrument segmentation in endoscopic spine surgery: cross-dataset evaluation under deployment-realistic conditions.

PURPOSE: Automated surgical instrument segmentation is a prerequisite for AI-assisted guidance in endoscopic spine surgery. Deployment-realistic compa...

Redefining breast cancer: therapeutic opportunities in HER2-low and emerging molecular subtypes.

Breast cancer classification has undergone significant evolution; however, the long-standing binary model distinguishing HER2-positive from HER2-negat...