Latest AI and machine learning research in covid-19 for healthcare professionals.
Multi-modal large language models (MLLMs) have achieved remarkable success in image- and region-level remote sensing (RS) image understanding tasks, such as image captioning, visual question answering, and visual grounding. However, existing RS MLLMs lack the pixel-level dialogue capability, which involves responding to user instructions with segmentation masks for specific instances. In this pa...
Although classical computing has excelled in a wide range of applications, there remain problems that push the limits of its capabilities, especially in fields like cryptography, optimization, and materials science. Quantum computing introduces a new computational paradigm, based on principles of superposition and entanglement to explore solutions beyond the capabilities of classical computation...
Deep learning methods - usually consisting of a class of deep neural networks (DNNs) trained by a stochastic gradient descent (SGD) optimization met...
This study demonstrates a novel approach to testing the security boundaries of Vision-Large Language Model (VLM/ LLM) using the EICAR test file embe...
The Ethereum blockchain has a \emph{gas system} that associates operations with a cost in gas units. Two central concepts of this system are the \em...
While most existing neural image compression (NIC) and neural video compression (NVC) methodologies have achieved remarkable success, their optimiza...
This study presents a comparative analysis of methods for detecting COVID-19 infection in radiographic images. The images, sourced from publicly ava...
Large Language Models integrating textual and visual inputs have introduced new possibilities for interpreting complex data. Despite their remarkabl...
Hypothesis testing is a statistical inference approach used to determine whether data supports a specific hypothesis. An important type is the two-s...
We consider the task of Image-to-Video (I2V) generation, which involves transforming static images into realistic video sequences based on a textual...
We present Ab-VS-Bench, a new benchmark for evaluating large language models (LLMs) on antibody virtual screening (VS) tasks through natural language ...
The brain exhibits rich oscillatory dynamics that play critical roles in vigilance and cognition, such as the neural rhythms that define sleep. These ...
Adeno-associated viruses (AAV) have emerged as a viable vector for gene therapy, with several clinical approvals and a growing pipeline in clinical tr...
We introduce HLAIIPred, a deep learning model to predict peptides presented by class II human leukocyte antigens (HLAII) on the surface of antigen pre...
Testing enhances memory more than studying. Although numerous studies have demonstrated the robustness of this classic effect, its neural and computat...
The analysis and prediction of antibody–antigen (Ab–Ag) interactions often overlook critical structural features such as glycosylation, physical chemi...
Cytosine and adenosine base editors show great potential in research and clinical applications. Current iterations of the deaminase—the enzyme used to...
AlphaFold has set a new standard for predicting protein structures from primary sequences; however, it faces challenges with protein complexes across ...
Given that influenza vaccine effectiveness depends on a good antigenic match between the vaccine and circulating viruses, it is important to assess th...
Single cell multi-omic investigation opens-up new opportunities to understand mechanisms of gene regulation. Existing methods for inferring transcript...