Hepatitis

Revolutionizing Personalized Cancer Vaccines with NEO: Novel Epitope Optimization Using an Aggregated Feed Forward and Recurrent Neural Network with LSTM Architecture

As cancer cases continue to rise, with a 2023 study from Zhejiang and Harvard predicting a 31 percent increase in cases and a 21 percent increase in deaths by 2030, the need to find more effective treatments for cancer is greater than ever before. Traditional approaches to treating cancer, such as chemotherapy, often kill healthy cells because of their lack of targetability. In contrast, persona...

Assessing Concordance between RNA-Seq and NanoString Technologies in Ebola-Infected Nonhuman Primates Using Machine Learning

This study evaluates the concordance between RNA sequencing (RNA-Seq) and NanoString technologies for gene expression analysis in non-human primates (NHPs) infected with Ebola virus (EBOV). We performed a detailed comparison of both platforms, demonstrating a strong correlation between them, with Spearman coefficients for 56 out of 62 samples ranging from 0.78 to 0.88, with a mean of 0.83 and a ...

Review on article of preoperative prediction in chronic hepatitis B virus patients using spectral computed tomography and machine learning.

This letter comments on the article that developed and tested a machine learning model that predicts lymphovascular invasion/perineural invasion statu...

Uncovering the Viral Nature of Toxicity in Competitive Online Video Games

Toxicity is a widespread phenomenon in competitive online video games. In addition to its direct undesirable effects, there is a concern that toxici...

Evaluation of alarm notification of artificial intelligence in automated analyzer detection of parasites.

To evaluate the alarm notification of artificial intelligence in detecting parasites on the KU-F40 Fully Automatic Feces Analyzer and provide a refere...

Development and validation of an explainable machine learning model for predicting multidimensional frailty in hospitalized patients with cirrhosis.

We sought to develop and validate a machine learning (ML) model for predicting multidimensional frailty based on clinical and laboratory data. Moreove...

MicroHDF: predicting host phenotypes with metagenomic data using a deep forest-based framework.

The gut microbiota plays a vital role in human health, and significant effort has been made to predict human phenotypes, especially diseases, with the...

Forecasting dominance of SARS-CoV-2 lineages by anomaly detection using deep AutoEncoders.

The COVID-19 pandemic is marked by the successive emergence of new SARS-CoV-2 variants, lineages, and sublineages that outcompete earlier strains, lar...

Decoding Style: Efficient Fine-Tuning of LLMs for Image-Guided Outfit Recommendation with Preference

Personalized outfit recommendation remains a complex challenge, demanding both fashion compatibility understanding and trend awareness. This paper p...

Structural causal influence (SCI) captures the forces of social inequality in models of disease dynamics

Mathematical modelling has served a central role in studying how infectious disease transmission manifests at the population level. These models hav...

Deep Learning Segmentation of Ascites on Abdominal CT Scans for Automatic Volume Quantification.

Purpose To evaluate the performance of an automated deep learning method in detecting ascites and subsequently quantifying its volume in patients with...

Antiviral Effectiveness, Clinical Outcomes, and Artificial Intelligence Imaging Analysis for Hospitalized COVID-19 Patients Receiving Antivirals.

INTRODUCTION: There is still a lack of clinical evidence comprehensively evaluating the effectiveness of antiviral treatments for COVID-19 hospitalize...

Establishment of diagnostic model and identification of diagnostic markers between liver cancer and cirrhosis based on multi-chip and machine learning.

OBJECTIVE: Most cases of hepatocellular carcinoma (HCC) arise as a consequence of cirrhosis. In this study, our objective is to construct a comprehens...

Surveillance of Health Care-Associated Violence Using Natural Language Processing.

BACKGROUND AND OBJECTIVES: Patient and family violent outbursts toward staff, caregivers, or through self-harm, have increased during the ongoing beha...

Exploiting Metabolic Defects in Glioma with Nanoparticle-Encapsulated NAMPT Inhibitors.

The treatment of primary central nervous system tumors is challenging due to the blood-brain barrier and complex mutational profiles, which is associa...

SecureVAX: A Blockchain-Enabled Secure Vaccine Passport System

A vaccine passport serves as documentary proof, providing passport holders with greater freedom while roaming around during pandemics. It confirms v...

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. ...

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...

HLAIImaster: a deep learning method with adaptive domain knowledge predicts HLA II neoepitope immunogenic responses.

While significant strides have been made in predicting neoepitopes that trigger autologous CD4+ T cell responses, accurately identifying the antigen p...

TP-LMMSG: a peptide prediction graph neural network incorporating flexible amino acid property representation.

Bioactive peptide therapeutics has been a long-standing research topic. Notably, the antimicrobial peptides (AMPs) have been extensively studied for i...