Latest AI and machine learning research in covid-19 for healthcare professionals.
Smartphone-based heart rate (HR) monitoring apps using finger-over-camera photoplethysmography (PP...
Existing feedforward subject-driven video customization methods mainly study single-subject scenar...
We present our solution for the Multi-Source COVID-19 Detection Challenge, which aims to classify ...
Collecting pixel-level labels for medical datasets can be a laborious and expensive process, and e...
Text-to-image retrieval (TIR) aims to find relevant images based on a textual query, but existing ...
Recent benchmarks reveal that models for single-cell perturbation response are often outperformed ...
Antibody design remains a critical challenge in therapeutic and diagnostic development, particular...
Few-shot fine-grained image classification (FS-FGIC) presents a significant challenge, requiring m...
Neoadjuvant chemoradiotherapy (NACRT) is the standard treatment for locally advanced rectal cancer (...
Large language models (LLMs) are increasingly used in clinical decision support, yet current evalu...
This article investigates matrix-free higher-order discontinuous Galerkin (DG) discretizations of ...
Auditory processing difficulties involve challenges in understanding speech in noisy environments ...
Masked-based autoregressive models have demonstrated promising image generation capability in cont...
Recent advances in deep learning have significantly propelled the development of image forgery loc...
Predicting the impact of genomic and drug perturbations in cellular function is crucial for unders...
Breast cancer remains a leading cause of cancer-related mortality worldwide, making early detectio...
In the past, the development of vaccines and immunotherapeutics relied heavily on trial-and-error ...
Designing protein-binding proteins with high affinity is critical in biomedical research and biote...
T cells targeting epitopes in infectious diseases or cancer play a central role in spontaneous and t...
The self-attention mechanism, a cornerstone of Transformer-based state-of-the-art deep learning ar...
Autoregressive generative models naturally generate variable-length sequences, while non-autoregre...