Infectious Disease

Multi-concept Model Immunization through Differentiable Model Merging

Model immunization is an emerging direction that aims to mitigate the potential risk of misuse associated with open-sourced models and advancing adaptation methods. The idea is to make the released models' weights difficult to fine-tune on certain harmful applications, hence the name ``immunized''. Recent work on model immunization focuses on the single-concept setting. However, models need to b...

Assessing the effectiveness of test-trace-isolate interventions using a multi-layered temporal network

In the early stage of an infectious disease outbreak, public health strategies tend to gravitate towards non-pharmaceutical interventions (NPIs) given the time required to develop targeted treatments and vaccines. One of the most common NPIs is Test-Trace-Isolate (TTI). One of the factors determining the effectiveness of TTI is the ability to identify contacts of infected individuals. In this st...

Diagnosising Helicobacter pylori using AutoEncoders and Limited Annotations through Anomalous Staining Patterns in IHC Whole Slide Images

Purpose: This work addresses the detection of Helicobacter pylori (H. pylori) in histological images with immunohistochemical staining. This analysi...

RCLMuFN: Relational Context Learning and Multiplex Fusion Network for Multimodal Sarcasm Detection

Sarcasm typically conveys emotions of contempt or criticism by expressing a meaning that is contrary to the speaker's true intent. Accurate detectio...

Multilabel Classification for Lung Disease Detection: Integrating Deep Learning and Natural Language Processing

Classifying chest radiographs is a time-consuming and challenging task, even for experienced radiologists. This provides an area for improvement due...

Adversarial Contrastive Domain-Generative Learning for Bacteria Raman Spectrum Joint Denoising and Cross-Domain Identification

Raman spectroscopy, as a label-free detection technology, has been widely utilized in the clinical diagnosis of pathogenic bacteria. However, Raman ...

DiffRaman: A Conditional Latent Denoising Diffusion Probabilistic Model for Bacterial Raman Spectroscopy Identification Under Limited Data Conditions

Raman spectroscopy has attracted significant attention in various biochemical detection fields, especially in the rapid identification of pathogenic...

MALrisk: a machine-learning-based tool to predict imported malaria in returned travellers with fever.

BACKGROUND: Early diagnosis is key to reducing the morbi-mortality associated with P. falciparum malaria among international travellers. However, acce...

A Misclassification Network-Based Method for Comparative Genomic Analysis

Classifying genome sequences based on metadata has been an active area of research in comparative genomics for decades with many important applicati...

CAD-Unet: A Capsule Network-Enhanced Unet Architecture for Accurate Segmentation of COVID-19 Lung Infections from CT Images

Since the outbreak of the COVID-19 pandemic in 2019, medical imaging has emerged as a primary modality for diagnosing COVID-19 pneumonia. In clinica...

SAMP: Identifying antimicrobial peptides by an ensemble learning model based on proportionalized split amino acid composition.

It is projected that 10 million deaths could be attributed to drug-resistant bacteria infections in 2050. To address this concern, identifying new-gen...

Multi-scale phylodynamic modelling of rapid punctuated pathogen evolution

Computational multi-scale pandemic modelling remains a major and timely challenge. Here we identify specific requirements for a new class of pandemi...

Utilizing Machine Learning Models to Predict Acute Kidney Injury in Septic Patients from MIMIC-III Database

Sepsis is a severe condition that causes the body to respond incorrectly to an infection. This reaction can subsequently cause organ failure, a majo...

BinSparX: Sparsified Binary Neural Networks for Reduced Hardware Non-Idealities in Xbar Arrays

Compute-in-memory (CiM)-based binary neural network (CiM-BNN) accelerators marry the benefits of CiM and ultra-low precision quantization, making th...

Stain-aware Domain Alignment for Imbalance Blood Cell Classification

Blood cell identification is critical for hematological analysis as it aids physicians in diagnosing various blood-related diseases. In real-world s...

Explaining the Unexplained: Revealing Hidden Correlations for Better Interpretability

Deep learning has achieved remarkable success in processing and managing unstructured data. However, its "black box" nature imposes significant limi...

Machine learning for adverse event prediction in outpatient parenteral antimicrobial therapy: a scoping review.

OBJECTIVE: This study aimed to conduct a scoping review of machine learning (ML) techniques in outpatient parenteral antimicrobial therapy (OPAT) for ...

Examining the Influenza A Virus Sialic Acid Binding Preference Predictions of a Sequence-Based Convolutional Neural Network.

BACKGROUND: Though receptor binding specificity is well established as a contributor to host tropism and spillover potential of influenza A viruses, d...

Survival causal rule ensemble method considering the main effect for estimating heterogeneous treatment effects.

With an increasing focus on precision medicine in medical research, numerous studies have been conducted in recent years to clarify the relationship b...

Deep Neural Network-Based Prediction of B-Cell Epitopes for SARS-CoV and SARS-CoV-2: Enhancing Vaccine Design through Machine Learning

The accurate prediction of B-cell epitopes is critical for guiding vaccine development against infectious diseases, including SARS and COVID-19. Thi...