Public Health

Prediction of Lung Metastasis from Hepatocellular Carcinoma using the SEER Database

Hepatocellular carcinoma (HCC) is a leading cause of cancer-related mortality, with lung metastases being the most common site of distant spread and significantly worsening prognosis. Despite the growing availability of clinical and demographic data, predictive models for lung metastasis in HCC remain limited in scope and clinical applicability. In this study, we develop and validate an end-to-e...

A CNN-Transformer for Classification of Longitudinal 3D MRI Images -- A Case Study on Hepatocellular Carcinoma Prediction

Longitudinal MRI analysis is crucial for predicting disease outcomes, particularly in chronic conditions like hepatocellular carcinoma (HCC), where early detection can significantly influence treatment strategies and patient prognosis. Yet, due to challenges like limited data availability, subtle parenchymal changes, and the irregular timing of medical screenings, current approaches have so far ...

Multi-View Transformers for Airway-To-Lung Ratio Inference on Cardiac CT Scans: The C4R Study

The ratio of airway tree lumen to lung size (ALR), assessed at full inspiration on high resolution full-lung computed tomography (CT), is a major ri...

VirusImmu: a novel ensemble machine learning approach for viral immunogenicity prediction.

The viruses threats provoke concerns regarding their sustained epidemic transmission, making the development of vaccines particularly important. In th...

A novel Facial Recognition technique with Focusing on Masked Faces

Recognizing the same faces with and without masks is important for ensuring consistent identification in security, access control, and public safety...

A causal machine-learning framework for studying policy impact on air pollution: a case study in COVID-19 lockdowns.

When studying the impact of policy interventions or natural experiments on air pollution, such as new environmental policies or the opening or closing...

Large Language Model-assisted text mining reveals bacterial pathogen diversity

Compiling and characterising the diversity of bacterial pathogens of humans is a critical challenge to tackle infection risk, especially in the contex...

SIMPLICITY: an agent-based, multi-scale mathematical model to study SARS-CoV-2 intra- and between-host evolution

Computational tools are frequently used to describe pathogen evolutionary dynamics either within infected hosts or at the population level. However, t...

Novel Computational Pipeline to Identify Target Sites for Broad Spectrum Antiviral Drugs

Emerging viruses pose an ongoing threat to human health. While certain viral families are common sources of outbreaks, predicting the specific virus w...

Language models learn to represent antigenic properties of human influenza A(H3) virus

Given that influenza vaccine effectiveness depends on a good antigenic match between the vaccine and circulating viruses, it is important to assess th...

CoV-UniBind: A Unified Antibody Binding Database for SARS-CoV-2

Since the emergence of SARS-CoV-2, numerous studies have investigated antibody interactions with viral variants in vitro, and several datasets have be...

WaveSeekerNet: Accurate Prediction of Influenza A Virus Subtypes and Host Source Using Attention-Based Deep Learning

Influenza A virus (IAV) poses a significant threat to animal health globally, with its ability to overcome species barriers and cause pandemics. Rapid...

Mapping antigenic evolution of influenza A virus using deep learning-based prediction of hemagglutination inhibition titers

Seasonal influenza remains a significant public health challenge through unpredictable antigenic drift, where accumulated mutations enable immune evas...

Reengineering the antigen optimization process for superior neoantigen vaccine design

Identifying effective neoantigen sequences is essential for enhancing anti-tumor immunity. However, the vast sequence space (>109 possible peptides) a...

From sequence to scaffold: computational design of protein nanoparticle vaccines from AlphaFold2-predicted building blocks

Self-assembling protein nanoparticles are being increasingly utilized in the design of next-generation vaccines due to their ability to induce antibod...

APDeeM: A machine Learning strategy towards Effective Peptide Vaccine Candidates Identification against Different Types of Viruses

Viral infections pose significant global health challenges, underscoring the urgent need for improved medications. Nevertheless, traditional medicinal...

Decoding the interconnected splicing patterns of hepatitis B virus and host using large language and deep learning models

Hepatitis B virus (HBV) infection causes approximately one million deaths annually and remains a major driver of hepatocellular carcinoma. Despite its...

A structure-informed evolutionary model for predicting viral immune escape and evolution

Persistent emergence of viral variants capable of evading host immunity constitutes a significant threat to public health. This antigenic evolution fr...

Influ-BERT: A Domain-Adaptive Genomic Language Model for Advancing Influenza A Virus Research

Influenza A Virus (IAV) poses a persistent threat to global public health due to its broad host adaptability, frequent anti-genic variation, and poten...

Fourier transform infrared spectroscopy enables rapid species discrimination across Malassezia and strain-level typing in M. pachydermatis

Malassezia pachydermatis is a zoophilic yeast found on the skin and in the outer ear canal of many mammals. It normally maintains a commensal lifestyl...