Latest AI and machine learning research in identifying and reporting dependent adult abuse for healthcare professionals.
Background: Population level assessments of predictive artificial intelligence (AI) can conceal performance disparities across subgroups. Fairness evaluations commonly rely on performance analyses across subgroups. However, some performance metrics are non-collapsible, meaning that the overall population performance value does not equal the weighted average of subgroup specific values. Objective...
Antiretroviral therapy (ART) stock-outs interrupt treatment, increase the risk of virologic failure and drug resistance, and erode the population-level benefits of viral suppression. India's National AIDS Control Organization (NACO) manages one of the world's largest public ART programmes, where regimen transitions, evolving formulations, changing treatment guidelines, and procurement-driven fluct...
Privacy-Enhancing Technologies (PETs) in computer vision often rely on noise or image perturbations to protect visual data while securely processing i...
Systematic reviews, scoping reviews, mapping studies, and related evidence syntheses are increasingly difficult to conduct with fully manual workflows...
Federated learning (FL) has emerged as a key approach for training models across decentralized data, yet benchmarking in FL remains difficult to repro...
Purpose: Automatic radiology report generation (RRG) has been widely explored to improve reporting accuracy and reduce radiologists' workload. Most ex...
Recently, the rapid advancement of multimodal domains has driven a data-centric paradigm shift in graph ML, transitioning from text-attributed to mult...
Single-cell drug perturbation models are increasingly used to predict how compounds remodel cellular states, but they are still largely assessed by ex...
Prostate cancer is among the most frequently diagnosed malignancies worldwide, and structured reporting of each biopsy core burdens pathologists. Exis...
BackgroundFive-year survival from lung cancer exceeds 60% at stage I-II but falls below 10% once metastasis occurs. Low-dose CT (LDCT) screening reduc...
Abstract Background: Every non-invasive continuous glucose monitoring (NI-CGM) technology introduced into the landscape faces the same skeptical quest...
Reliable endoscopic polyp reporting requires integrating quantitative lesion sizing, standardized Paris classification, and clinically meaningful morp...
Thyroid ultrasound diagnosis requires coordinated lesion localization, measurement, risk stratification and reporting, yet most AI systems address the...
In medical imaging, the clinical value of Computed Tomography (CT) lies not only in depicting current disease status, but crucially in enabling longit...
Existing diffusion-based methods have recently made significant progress in image dehazing. However, they typically neglect the physics of haze format...
This paper presents RobustDefect-LLM, an industrial surface-defect inspection framework integrating deep-learning classification, operator-facing visu...
The continuous accumulation of genetic mutations in influenza A viruses (IAVs) drives antigenic drift, necessitating precise antigenic prediction for ...
Thermochemical upgrading of plastic waste is a key upcycling pathway, yet the experimental literature is fragmented by heterogeneous conditions and in...
The rapid advancement of image generation models has made it increasingly difficult for people to distinguish AI-generated images from real ones. To p...
Recent advances in 3D Gaussian Splatting (3DGS)-based wireless radiance field (WRF) reconstruction provide an efficient solution for wireless channel ...