Infectious Disease

The Lifetime of the Covid Memorial Wall: Modelling with Collections Demography, Social Media Data and Citizen Science

The National Covid Memorial Wall in London, featuring over 240,000 hand-painted red hearts, faces significant conservation challenges due to the rapid fading of the paint. This study evaluates the transition to a better-quality paint and its implications for the wall's long-term preservation. The rapid fading of the initial materials required an unsustainable repainting rate, burdening volunteer...

AI-guided Antibiotic Discovery Pipeline from Target Selection to Compound Identification

Antibiotic resistance presents a growing global health crisis, demanding new therapeutic strategies that target novel bacterial mechanisms. Recent advances in protein structure prediction and machine learning-driven molecule generation offer a promising opportunity to accelerate drug discovery. However, practical guidance on selecting and integrating these models into real-world pipelines remain...

Inferring genotype-phenotype maps using attention models

Predicting phenotype from genotype is a central challenge in genetics. Traditional approaches in quantitative genetics typically analyze this proble...

Reconstructing Sepsis Trajectories from Clinical Case Reports using LLMs: the Textual Time Series Corpus for Sepsis

Clinical case reports and discharge summaries may be the most complete and accurate summarization of patient encounters, yet they are finalized, i.e...

Graph-Based Prediction Models for Data Debiasing

Bias in data collection, arising from both under-reporting and over-reporting, poses significant challenges in critical applications such as healthc...

Accurate Diagnosis of Respiratory Viruses Using an Explainable Machine Learning with Mid-Infrared Biomolecular Fingerprinting of Nasopharyngeal Secretions

Accurate identification of respiratory viruses (RVs) is critical for outbreak control and public health. This study presents a diagnostic system tha...

On Transfer-based Universal Attacks in Pure Black-box Setting

Despite their impressive performance, deep visual models are susceptible to transferable black-box adversarial attacks. Principally, these attacks c...

Boosting multi-demographic federated learning for chest x-ray analysis using general-purpose self-supervised representations

Reliable artificial intelligence (AI) models for medical image analysis often depend on large and diverse labeled datasets. Federated learning (FL) ...

The Efficacy of Semantics-Preserving Transformations in Self-Supervised Learning for Medical Ultrasound

Data augmentation is a central component of joint embedding self-supervised learning (SSL). Approaches that work for natural images may not always b...

Novel Pooling-based VGG-Lite for Pneumonia and Covid-19 Detection from Imbalanced Chest X-Ray Datasets

This paper proposes a novel pooling-based VGG-Lite model in order to mitigate class imbalance issues in Chest X-Ray (CXR) datasets. Automatic Pneumo...

Parasite: A Steganography-based Backdoor Attack Framework for Diffusion Models

Recently, the diffusion model has gained significant attention as one of the most successful image generation models, which can generate high-qualit...

ViralQC: A Tool for Assessing Completeness and Contamination of Predicted Viral Contigs

Motivation: Viruses represent the most abundant biological entities on the planet and play vital roles in diverse ecosystems. Cataloging viruses acr...

Evaluating the Impact of the EU AI Act on Medical Device Regulation.

Artificial Intelligence (AI) is increasingly incorporated into medical devices, revolutionizing diagnostics, treatment planning, and patient monitorin...

Artificial neural networks to predict the presence of Neosporosis in cattle.

The prediction of bovine infectious diseases is a constant challenge as generally, only laboratory data is available not allowing the study of their r...

Noninvasive prediction of esophagogastric varices in hepatitis B: An extreme gradient boosting model based on ultrasound and serology.

BACKGROUND: Severe esophagogastric varices (EGVs) significantly affect prognosis of patients with hepatitis B because of the risk of life-threatening ...

A Comprehensive Survey of Challenges and Opportunities of Few-Shot Learning Across Multiple Domains

In a world where new domains are constantly discovered and machine learning (ML) is applied to automate new tasks every day, challenges arise with t...

Multi-encoder nnU-Net outperforms Transformer models with self-supervised pretraining

This study addresses the essential task of medical image segmentation, which involves the automatic identification and delineation of anatomical str...

Task as Context Prompting for Accurate Medical Symptom Coding Using Large Language Models

Accurate medical symptom coding from unstructured clinical text, such as vaccine safety reports, is a critical task with applications in pharmacovig...

Robust Diagnosis of Acute Bacterial and Viral Infections via Host Gene Expression Rank-Based Ensemble Machine Learning Algorithm: A Multi-Cohort Model Development and Validation Study.

BACKGROUND: The accurate and prompt diagnosis of infections is essential for improving patient outcomes and preventing bacterial drug resistance. Host...

Horizon Scans can be accelerated using novel information retrieval and artificial intelligence tools

Introduction: Horizon scanning in healthcare assesses early signals of innovation, crucial for timely adoption. Current horizon scanning faces chall...