Latest AI and machine learning research in covid-19 for healthcare professionals.
Visual counterfactual explanations aim to change classifier decisions through realistic and localized edits while preserving decision-irrelevant content. Existing DDPM-based methods typically perform classifier-guided editing along a long reverse denoising trajectory. The changing noise levels make semantic editability and spatial control difficult to balance, and the editable state is noisy, wher...
Accurately predicting the effects of pharmacogenomic variants is essential for the development of personalized therapeutic strategies, as genetic variability can influence drug response differently across patients. Here, we assessed several computational approaches using a dataset of pharmacogenomic variants with either clinical annotations or functional characterization by deep mutational scannin...
The COVID-19 pandemic triggered an unprecedented volume of real-time discourse on social media platforms, with Twitter serving as a global forum for p...
The continuous accumulation of genetic mutations in influenza A viruses (IAVs) drives antigenic drift, necessitating precise antigenic prediction for ...
Deleting a gene token from a cell's input sequence offers a convenient native strategy for in silico perturbation, but the resulting embedding delta m...
Inherited lung cancer risk arises from both protein-coding and non-coding germline variants, but the functional non-coding component is largely unchar...
SAM3 extends promptable segmentation from geometry-driven mask prediction to open-vocabulary concept segmentation, where a text-conditioned grounding ...
Oral health issues affect billions globally, but the cost and limited access to professional dental care hinder preventive oral healthcare. Research r...
Multibodies, or "two-in-one" Immunoglobulin G (IgG) antibodies, are standard symmetrical IgG molecules engineered to competitively bind more than one ...
The emergence of medical deepfakes, i.e., medical images manipulated by deep generative models, poses a significant threat to clinical workflows. Howe...
Multimodal large language models (MLLMs) make grounded predictions in real-world scenes by combining visual and textual cues, yet existing benchmarks ...
The human immune system excels at generating highly effective antibodies through natural selection and somatic hypermutation, but adapting these antib...
Controllable local editing of 3D assets requires precise target localization and appropriate visual guidance. However, existing methods lack a simple ...
Precise anomaly localization over long-context time series is a crucial task in monitoring applications across clinical care, industrial operations, f...
Deepfake technologies pose increasing threats to facial privacy and identity security, motivating proactive defenses that protect facial images before...
One common approach to pose estimation involves predicting object keypoints in an image, followed by using Perspective-n-Point algorithms to compute t...
Terminal User Interfaces (TUIs) combine the stateful, screen-oriented behaviour of GUIs with terminal deployment and are now common in developer tools...
MLLM-based segmentation faces a core segmentation trilemma: high segmentation performance, preserved dialogue ability, and fast inference. Embedding-p...
Ask a commercial image editor to preview a cosmetic procedure and it will often change more of the face than the request names: a nose edit can also s...
Background: Precision oncology relies on accurate interpretation of tumour-detected gene variants, to guide personalized treatment decisions. However,...