Devices and Vaccines

Precision Imaging to Evaluate Kaposi Sarcoma (PRIME-KS): protocol for a multicountry novel artificial intelligence-based imaging device

Abstract Background: Kaposi sarcoma (KS) is the most common cancer among men in several Eastern African countries, yet treatment monitoring relies on imprecise, time-consuming ruler-based measurements defined by the AIDS Clinical Trial Group (ACTG). This method suffers from inter-observer variability, fails to capture lesion height or true geometric area, and performs poorly on dark skin. SkinScan...

Prototyping a Generative AI-powered Person-centered Digital Health Tool to Mitigate Risk of Preventable Adverse Drug Events

Objectives: Older adults with comorbidities and polypharmacy have disproportionately high risk of hospitalization as well as readmission from adverse drug events (ADEs), of which 28%-71% are preventable (pADEs). This paper introduces an LLM application, CommunicADE, designed to support risk-mitigation of pADE-related readmission for the aforementioned population. We aim to evaluate CommunicADE's t...

Agentic Authoring of OMOP Concept Sets from Natural Language

Authoring OMOP concept sets from free-text descriptions remains a major bottleneck in scalable computable phenotyping for observational research. Exis...

The AFRIDIARRHEA multimodal fusion framework for Estimating the Burden of Diarrheal Diseases Among Children Under Five in Kenya, Zimbabwe, and Somaliland

Background: Accurate estimation of childhood diarrheal disease burden in Africa remains challenging because of limited surveillance, incomplete mortal...

Relationship Extraction for Adverse Drug Events in Clinical Notes Using Large Language Models

Background: Adverse drug events (ADEs) are a critical indicator of patient safety but are often documented only in free-text clinical notes. The poten...

Design and structure of protein cages based on helical fusion and machine learning

Self-assembling protein cages are versatile nanoscale architectures with broad applications in drug delivery, vaccine development, and structural biol...

Intact early visual representations, not phosphene-adapted features, account for human perceptual behavior with retinal prostheses

Efforts to restore vision via neural implants have outpaced the ability to predict what users will perceive, leaving patients and clinicians without r...

geneML: Gene annotation across diverse fungal species using deep learning

Accurate gene prediction remains a major bottleneck in fungal genomics, where lineage diversity and alternative splicing challenge existing ab initio ...

Membrane proteomics of the Drosophila circadian neural network

Circadian behaviors are controlled by dedicated brain pacemaker neurons, whose activity oscillate during the day and the night. The Drosophila brain c...

GraphMAR: Geometry-Aware Graph Learning Framework for Spatially Adaptive CT Metal Artifact Reduction

Computed tomography (CT) metal artifact reduction (MAR) aims to reduce the severe streaking artifacts induced by metallic implants and other high-dens...

Smartphone Placement Recognition during Walking: Performance Determinants and Real-World Generalizability

The opportunity to collect movement data from smartphones for prolonged periods has opened new perspectives in the field of clinical movement analysis...

Road Maps as Free Geometric Priors: Weather-Invariant Drone Geo-Localization with GeoFuse

Drone-view geo-localization aims to match a query drone image, often captured under adverse weather conditions (e.g., rain, snow, fog), against a gall...

HAIRpred2: Human Host-Specific Prediction of Antibody-Interacting Residues Using Hybrid Physicochemical and Structural Features

Prediction of conformational B-cell epitopes is critical for vaccine design, immunotherapy, and antibody engineering. To date, several host-independen...

Urban Risk-Aware Navigation via VQA-Based Event Maps for People with Low Vision

Visual impairment affects hundreds of millions of people worldwide, severely limiting their ability to navigate urban environments safely and independ...

Development of a Deep Learning Model Integrating CT Images and Blood Data for the Diagnosis of Acute Cholecystitis

Purpose: In this study, we aimed to develop and evaluate an artificial intelligence-based diagnostic model for the diagnosis of acute cholecystitis (A...

Three Decades of FDA Authorizations of AI/ML Enabled Medical Devices: Persistent Specialty Concentration and the Care Delivery Gap (1995 to 2025)

The US Food and Drug Administration (FDA) maintains a public list of artificial intelligence and machine learning (AI/ML)-enabled medical devices that...

AI-enabled virtual immunopeptidomics links quantitative neoantigen presentation to immunogenicity

Effective anti-tumor T cell response depends on both neoantigen quality (non-selfness) and quantity (abundance). However, existing methods for neoanti...

Backdoor Mitigation in Object Detection via Adversarial Fine-Tuning

Backdoor attacks can implant malicious behaviours into deep models while preserving performance on clean data, posing a serious threat to safety-criti...

Deep Learning-Based Structure Modeling of the Treponema pallidum Proteome: Insights into Pathogenesis and Syphilis Vaccine Development

Treponema pallidum ssp. pallidum, the causative agent of syphilis, has a small proteome and encompasses numerous strains. Knowledge gaps remain in und...

Extracting adverse event nature, severity, timelines and resulting interventions from clinical notes of patients receiving CAR-T therapy using large language models.

Chimeric Antigen Receptor T-cell (CAR-T) therapy, where genetically engineered patient T cells target tumor antigens, has transformed care for hematol...