Infectious Disease

COVID-19

Latest AI and machine learning research in covid-19 for healthcare professionals.

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Showing 4941-4960 of 8,596 articles

Anatomy-Informed Deep Learning and Radiomics for Automated Neurofibroma Segmentation in Whole-Body MRI

Neurofibromatosis Type 1 is a genetic disorder characterized by the development of neurofibromas (NFs), which exhibit significant variability in size, morphology, and anatomical location. Accurate and automated segmentation of these tumors in whole-body magnetic resonance imaging (WB-MRI) is crucial to assess tumor burden and monitor disease progression. In this study, we present and analyze a f...

Soybean pod and seed counting in both outdoor fields and indoor laboratories using unions of deep neural networks

Automatic counting soybean pods and seeds in outdoor fields allows for rapid yield estimation before harvesting, while indoor laboratory counting offers greater accuracy. Both methods can significantly accelerate the breeding process. However, it remains challenging for accurately counting pods and seeds in outdoor fields, and there are still no accurate enough tools for counting pods and seeds ...

Assessing a Single Student's Concentration on Learning Platforms: A Machine Learning-Enhanced EEG-Based Framework

This study introduces a specialized pipeline designed to classify the concentration state of an individual student during online learning sessions b...

RelaCtrl: Relevance-Guided Efficient Control for Diffusion Transformers

The Diffusion Transformer plays a pivotal role in advancing text-to-image and text-to-video generation, owing primarily to its inherent scalability....

Optimizing Gene-Based Testing for Antibiotic Resistance Prediction

Antibiotic Resistance (AR) is a critical global health challenge that necessitates the development of cost-effective, efficient, and accurate diagno...

Domination in Graph Theory: A Bibliometric Analysis of Research Trends, Collaboration and Citation Networks

This study conducts a comprehensive bibliometric analysis of research on domination in graph theory from 1961 to 2024, based on Scopus-indexed publi...

PTQ1.61: Push the Real Limit of Extremely Low-Bit Post-Training Quantization Methods for Large Language Models

Large Language Models (LLMs) suffer severe performance degradation when facing extremely low-bit (sub 2-bit) quantization. Several existing sub 2-bi...

UniMatch: Universal Matching from Atom to Task for Few-Shot Drug Discovery

Drug discovery is crucial for identifying candidate drugs for various diseases.However, its low success rate often results in a scarcity of annotati...

WRT-SAM: Foundation Model-Driven Segmentation for Generalized Weld Radiographic Testing

Radiographic testing is a fundamental non-destructive evaluation technique for identifying weld defects and assessing quality in industrial applicat...

Self-supervised Attribute-aware Dynamic Preference Ranking Alignment

Reinforcement Learning from Human Feedback and its variants excel in aligning with human intentions to generate helpful, harmless, and honest respon...

PromptArtisan: Multi-instruction Image Editing in Single Pass with Complete Attention Control

We present PromptArtisan, a groundbreaking approach to multi-instruction image editing that achieves remarkable results in a single pass, eliminatin...

Leveraging Machine Learning and Deep Learning Techniques for Improved Pathological Staging of Prostate Cancer

Prostate cancer (Pca) continues to be a leading cause of cancer-related mortality in men, and the limitations in precision of traditional diagnostic...

Towards Fine-grained Interactive Segmentation in Images and Videos

The recent Segment Anything Models (SAMs) have emerged as foundational visual models for general interactive segmentation. Despite demonstrating rob...

Hierarchical Entropy Disruption for Ransomware Detection: A Computationally-Driven Framework

The rapid evolution of encryption-based threats has rendered conventional detection mechanisms increasingly ineffective against sophisticated attack...

Towards More Accurate Full-Atom Antibody Co-Design

Antibody co-design represents a critical frontier in drug development, where accurate prediction of both 1D sequence and 3D structure of complementa...

A Simple yet Effective DDG Predictor is An Unsupervised Antibody Optimizer and Explainer

The proteins that exist today have been optimized over billions of years of natural evolution, during which nature creates random mutations and sele...

KMT2B-related disorders: expansion of the phenotypic spectrum and long-term efficacy of deep brain stimulation

Heterozygous mutations in KMT2B are associated with an early-onset, progressive, and often complex dystonia (DYT28). Key characteristics of typical ...

Make the Fastest Faster: Importance Mask for Interactive Volume Visualization using Reconstruction Neural Networks

Visualizing a large-scale volumetric dataset with high resolution is challenging due to the high computational time and space complexity. Recent dee...

Delta -- Contrastive Decoding Mitigates Text Hallucinations in Large Language Models

Large language models (LLMs) demonstrate strong capabilities in natural language processing but remain prone to hallucinations, generating factually...

BodySense: An Expandable and Wearable-Sized Wireless Evaluation Platform for Human Body Communication

Wearable, wirelessly connected sensors have become a common part of daily life and have the potential to play a pivotal role in shaping the future o...

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