Latest AI and machine learning research in devices and vaccines for healthcare professionals.
Prediction of B-cell epitopes can assist in reducing costly wet-lab screening in vaccine design, diagnostics, and antibody discovery. However, current predictors often suffer from noisy labels, weak generalization, and structure-dependent workflows. Here we present EPIESM-GA, an efficient sequence-only pipeline for linear B-cell epitope prediction. Positive and negative peptide examples are collec...
Medical device recalls are a critical regulatory mechanism for protecting patient safety. The growing volume of FDA recall records presents challenges in post-report recall triage, severity assessment, and root-cause interpretation. Existing studies mostly address recall occurrence prediction or root-cause analysis separately, while joint modeling of recall severity and root-cause categories has r...
Understanding brain-behavior relationships requires models capturing the distributed, interactive, and multiscale nature of neural systems. Traditiona...
Predicting how mutations alter antibody-antigen binding affinity is essential for antibody engineering and vaccine design, yet current methods general...
Clinical value sets define the standardized terminology codes used in quality measurement, phenotyping, cohort construction, and clinical decision sup...
Seasonal influenza A evolves rapidly, allowing newly emerged clades to replace previously dominant lineages and complicate surveillance and vaccine ev...
Vaccine antigen discovery requires prioritizing protein candidates according to both immunogenic potential and recombinant expression feasibility. The...
Fine-tuning can adapt pretrained medical imaging models to new clinical datasets, but device-specific domain shifts may limit generalizability. We eva...
Objective. To preserve the encoding of visual information in prosthetic vision as close to natural as possible, subretinal photovoltaic implants, whic...
Physical events are not understood by their names alone, but by the causal state changes that compose them. A clip-level label such as "bounce" can be...
Despite recent advancements in deep learning, accurately classifying brain tumors from MRI images continues to pose challenges. In this research, we p...
Long-term mortality rates after endovascular aneurysm repair (EVAR) remain elevated due to post-EVAR rupture caused by loss of seal in stent graft sea...
A key challenge in multimodal reasoning is determining which visual dependencies become relevant under a specific task, rather than merely recognizing...
Building trustworthy medical multimodal large language models (MLLMs) is critical for reliable clinical decision support. Existing medical hallucinati...
Background and rationale: Knee osteoarthritis (KOA) is a leading cause of lower limb disability worldwide, characterized by functional limitations, st...
Objective. Figure copy and recall tests are sensitive measures of visuoconstruction and visual episodic memory, but their clinical is constrained by l...
**Abstract** **Background:** Transcatheter edge-to-edge repair (TEER) is an established treatment for mitral regurgitation but remains highly dependen...
Large language models embedded in autonomous agents process trusted instructions and untrusted data in one context window, leaving them open to direct...
Background: The expansion of biomedical literature demands systematic ontology-guided discovery of gene interactions, vaccine mechanisms, drug associa...
Joint contact forces govern implant longevity, cartilage health, and rehabilitation outcomes, shaping who develops osteoarthritis, who recovers well f...