Infectious Disease

Protein function prediction using GO similarity-based heterogeneous network propagation.

Protein function prediction is a fundamental cornerstone in bioinformatics, providing critical insights into biological processes and disease mechanisms. Despite significant advances, challenges persist due to data sparsity and functional ambiguity. We introduce GOHPro (GO Similarity-based Heterogeneous Network Propagation), a novel method that constructs a heterogeneous network by integrating pro...

Disc Diffusion Reader: an AI-powered potential solution to combat antibiotic resistance in developing countries.

INTRODUCTION: Antimicrobial resistance (AMR) is a global health challenge, and antimicrobial susceptibility testing (AST) is vital for guiding treatment. Although widely used, the Kirby-Bauer method depends on skilled interpretation, which can be time-intensive and error-prone. This study explored the potential of an artificial intelligence (AI)-driven progressive web app (PWA) to automate the ana...

Intelligent Prediction Platform for Sepsis Risk Based on Real-Time Dynamic Temporal Features: Design Study.

BACKGROUND: The development of sepsis in the intensive care unit (ICU) is rapid, the golden rescue time is short, and the effective way to reduce mort...

An efficient plant disease detection using transfer learning approach.

Plant diseases pose significant challenges to farmers and the agricultural sector at large. However, early detection of plant diseases is crucial to m...

Dc-EEMF: Pushing depth-of-field limit of photoacoustic microscopy via decision-level constrained learning

Photoacoustic microscopy holds the potential to measure biomarkers' structural and functional status without labels, which significantly aids in com...

CNN-LSTM Hybrid Model for AI-Driven Prediction of COVID-19 Severity from Spike Sequences and Clinical Data

The COVID-19 pandemic, caused by SARS-CoV-2, highlighted the critical need for accurate prediction of disease severity to optimize healthcare resour...

Model Immunization from a Condition Number Perspective

Model immunization aims to pre-train models that are difficult to fine-tune on harmful tasks while retaining their utility on other non-harmful task...

Patient Domain Supervised Contrastive Learning for Lung Sound Classification Using Mobile Phone

Auscultation is crucial for diagnosing lung diseases. The COVID-19 pandemic has revealed the limitations of traditional, in-person lung sound assess...

Identification of novel therapeutic targets in hepatitis-B virus-associated membranous nephropathy using scRNA-seq and machine learning.

Hepatitis B Virus-associated membranous nephropathy (HBV-MN) significantly impacts renal health, particularly in areas with high HBV prevalence. Under...

Development and Validation of SXI++ LNM Algorithm for Sepsis Prediction

Sepsis is a life-threatening condition affecting over 48.9 million people globally and causing 11 million deaths annually. Despite medical advanceme...

Investigating the effectiveness of multimodal data in forecasting SARS-COV-2 case surges

The COVID-19 pandemic response relied heavily on statistical and machine learning models to predict key outcomes such as case prevalence and fatalit...

Chest Disease Detection In X-Ray Images Using Deep Learning Classification Method

In this work, we investigate the performance across multiple classification models to classify chest X-ray images into four categories of COVID-19, ...

Test-Time Immunization: A Universal Defense Framework Against Jailbreaks for (Multimodal) Large Language Models

While (multimodal) large language models (LLMs) have attracted widespread attention due to their exceptional capabilities, they remain vulnerable to...

VIRAL: Vision-grounded Integration for Reward design And Learning

The alignment between humans and machines is a critical challenge in artificial intelligence today. Reinforcement learning, which aims to maximize a...

VIRAL: Vision-grounded Integration for Reward design And Learning

The alignment between humans and machines is a critical challenge in artificial intelligence today. Reinforcement learning, which aims to maximize a...

Scalable and robust machine learning framework for HIV classification using clinical and laboratory data.

Human Immunodeficiency Virus (HIV) is a retrovirus that weakens the immune system, increasing vulnerability to infections and cancers. HIV spreads pri...

Drug repurposing targeting COVID-19 3CL protease using molecular docking and machine learning regression approaches.

The COVID-19 pandemic has initiated a global health emergency, with an exigent need for an effective cure. Progressively, drug repurposing is emerging...

FCOS: A Two-Stage Recoverable Model Pruning Framework for Automatic Modulation Recognition

With the rapid development of wireless communications and the growing complexity of digital modulation schemes, traditional manual modulation recogn...

A Framework for Adversarial Analysis of Decision Support Systems Prior to Deployment

This paper introduces a comprehensive framework designed to analyze and secure decision-support systems trained with Deep Reinforcement Learning (DR...

Identifying Heart Attack Risk in Vulnerable Population: A Machine Learning Approach

The COVID-19 pandemic has significantly increased the incidence of post-infection cardiovascular events, particularly myocardial infarction, in indi...