Infectious Disease

Observation of Aerosolization-induced Morphological Changes in Viral Capsids

Single-stranded RNA viruses co-assemble their capsid with the genome and variations in capsid structures can have significant functional relevance. In particular, viruses need to respond to a dehydrating environment to prevent genomic degradation and remain active upon rehydration. Theoretical work has predicted low-energy buckling transitions in icosahedral capsids which could protect the virus...

No Train, all Gain: Self-Supervised Gradients Improve Deep Frozen Representations

This paper introduces FUNGI, Features from UNsupervised GradIents, a method to enhance the features of transformer encoders by leveraging self-supervised gradients. Our method is simple: given any pretrained model, we first compute gradients from various self-supervised objectives for each input. These gradients are projected to a lower dimension and then concatenated with the model's output emb...

Microbial and Viral Ecology Analysis for Metagenomic Data

The explosion in known microbial diversity in the last two decades has made it abundantly clear that microbes in the environment do not exist in iso...

Pseudo-perplexity in One Fell Swoop for Protein Fitness Estimation

Protein language models trained on the masked language modeling objective learn to predict the identity of hidden amino acid residues within a seque...

New Directions in Text Classification Research: Maximizing The Performance of Sentiment Classification from Limited Data

The stakeholders' needs in sentiment analysis for various issues, whether positive or negative, are speed and accuracy. One new challenge in sentime...

Synthetic data: How could it be used for infectious disease research?

Over the last three to five years, it has become possible to generate machine learning synthetic data for healthcare-related uses. However, concerns...

M5: A Whole Genome Bacterial Encoder at Single Nucleotide Resolution

A linear attention mechanism is described to extend the context length of an encoder only transformer, called M5 in this report, to a multi-million ...

Development of Machine Learning Classifiers for Blood-based Diagnosis and Prognosis of Suspected Acute Infections and Sepsis

We applied machine learning to the unmet medical need of rapid and accurate diagnosis and prognosis of acute infections and sepsis in emergency depa...

CGRclust: Chaos Game Representation for Twin Contrastive Clustering of Unlabelled DNA Sequences

This study proposes CGRclust, a novel combination of unsupervised twin contrastive clustering of Chaos Game Representations (CGR) of DNA sequences, ...

A deep learning method to predict bacterial ADP-ribosyltransferase toxins.

MOTIVATION: ADP-ribosylation is a critical modification involved in regulating diverse cellular processes, including chromatin structure regulation, R...

Unravelling tumour cell diversity and prognostic signatures in cutaneous melanoma through machine learning analysis.

Melanoma, a highly malignant tumour, presents significant challenges due to its cellular heterogeneity, yet research on this aspect in cutaneous melan...

Structure-aware deep learning model for peptide toxicity prediction.

Antimicrobial resistance is a critical public health concern, necessitating the exploration of alternative treatments. While antimicrobial peptides (A...

Towards Fluorescent-Tag-Less Viral Titration: Automated Estimation of Cell-Size Distribution and Infection Level from Phase-Contrast Microscopy Using Deep Learning and Transfer Learning.

Automated detection of infected insect cells is one of the crucial tasks in the field of recombinant protein production and vaccine development. The m...

Detection of hospital super bacteria MRSA from the hands of healthcare professionals using machine learning and hyperspectral imaging.

Healthcare-associated infections resulting from cross-contamination, particularly from the hands of multidisciplinary staff, significantly impact pati...

Cough Sound Based Deep Learning Models for Diagnosis of COVID-19 Using Statistical Features and Time-Frequency Spectrum.

This paper presents a deep learning model that can classify COVID-19 patients through cough sounds. The cough sound data were selected from the Cambri...

Cough Classification of Unknown Emerging Respiratory Disease with Federated Learning.

Artificial intelligence offers great potential to address the need for rapid diagnostic testing in pandemic scenarios. Concerns about security and pri...

An Explainable Transfer Learning Method for EEG-based Seizure Type Classification.

Epilepsy, traditionally conceptualized as a neurological disorder characterized by a persistent inclination toward epileptic seizures, is commonly dia...

Automatic COVID-19 Detection from Chest X-ray using Deep MobileNet Convolutional Neural Network.

As the COVID-19 pandemic has put a strain on healthcare systems around the world, accurate and rapid virus detection has become increasingly important...

Time-varying compartmental models with neural networks for pandemic infection forecasting.

The emergence and spread of deadly pandemics has repeatedly occurred throughout history, causing widespread infections and life loss. Forecasting the ...

Leveraging Graph Neural Networks for MIC Prediction in Antimicrobial Resistance Studies.

Antimicrobial resistance (AMR) poses a significant challenge in healthcare and public health, with organisms such as nontyphoidal Salmonella leading t...