Latest AI and machine learning research in medicare for healthcare professionals.
The rise of home-deployed embodied AI systems is driving a growing need for fast, metric 3D reconstruction of residential spaces to support navigation, interaction, and long-horizon task execution. However, the commonly used pinhole-camera 3D reconstruction pipelines struggle to model large indoor residences efficiently due to their limited field of view, to which achieving full coverage across mu...
Conformal predictions have attracted significant attention in the field of uncertainty quantification, mainly because of their strong marginal coverage guarantees. Full conditional guarantee is not an attainable goal, a well known fact in conformal predictions literature. As a result, several approaches have tried to approximate this behavior by adapting the conformal sets of test-time samples acc...
Structured tabular data dominates clinical medicine, yet existing benchmarks fail to reflect real-world properties like complex survey sampling, demog...
Timely intensive care dictates survival, yet emergency infrastructure remains unevenly distributed across Sri Lanka. While pre-hospital services have ...
Constructing simulation-ready 3D scenes from multi-view captures is a key bottleneck for Embodied Artificial Intelligence, as downstream tasks require...
Attributing a generated image to its source diffusion model is a fundamental challenge in provenance verification and intellectual property protection...
Wildfire monitoring from UAVs requires reliable reasoning over complex aerial scenes, where smoke, scale variation, and occlusions often limit RGB-onl...
Recent image generation models achieve impressive quality in single-image synthesis, but often fail to maintain consistency across sequential outputs,...
A robot working alongside people must reason about what they have done, in what order, and with what intent. Video carries the spatial layouts, object...
Diffusion models have achieved strong performance in image, text-to-image, and video generation, where conditional generation is often controlled by c...
Purpose: To investigate how artificial intelligence (AI) systems detect referrable diabetic retinopathy (DR) from retinal photographs by analysing hea...
Modeling long-sequence medical time series data, such as electrocardiograms (ECG), poses significant challenges due to high sampling rates, multichann...
Nickel has been studied for a long time as an environmental contaminant but less so in its connection to population health. It does not announce itsel...
Composed image retrieval (CIR) uses a reference image and a text modification to search for a target image. However, such queries often describe sever...
Alternative isoform usage can alter gene function independently of total gene expression, creating a need to resolve transcript isoforms at single-cel...
Coastal algal bloom monitoring requires frequent, spatially detailed, and globally consistent observations, provided by Landsat-8/9 and Sentinel-2 A/B...
Large vision-language models (LVLMs) hallucinate: they assert visual details that the image does not support. A principled remedy is selective predict...
Background and rationale: Knee osteoarthritis (KOA) is a leading cause of lower limb disability worldwide, characterized by functional limitations, st...
Remote photoplethysmography (rPPG) transformers achieve low heart-rate error on benchmarks, yet their decisions remain opaque--a growing concern as rP...
Diffusion models have emerged as state-of-the-art generative models for high-fidelity image synthesis, particularly in their classifier-free guided an...