Infectious Disease

Modulating autophagy to treat diseases: A revisited review on in silico methods.

BACKGROUND: Autophagy refers to the conserved cellular catabolic process relevant to lysosome activity and plays a vital role in maintaining the dynamic equilibrium of intracellular matter by degrading harmful and abnormally accumulated cellular components. Accumulating evidence has recently revealed that dysregulation of autophagy by genetic and exogenous interventions may disrupt cellular homeos...

Deep learning PET/CT-based radiomics integrates clinical data: A feasibility study to distinguish between tuberculosis nodules and lung cancer.

BACKGROUND: Radiomic diagnosis models generally consider only a single dimension of information, leading to limitations in their diagnostic accuracy and reliability. The integration of multiple dimensions of information into the deep learning model have the potential to improve its diagnostic capabilities. The purpose of study was to evaluate the performance of deep learning model in distinguishin...

Fingerprint-Enhanced Graph Attention Network (FinGAT) Model for Antibiotic Discovery.

Artificial Intelligence (AI) techniques are of great potential to fundamentally change antibiotic discovery industries. Efficient and effective molecu...

Analytical and clinical performance evaluation of enhanced chemiluminescence-based fourth-generation HIV combo assay: Report from tertiary health-care setup in North India.

INTRODUCTION: HIV fourth-generation assay, designed for the detection of HIV p24 antigen along with anti-HIV antibodies of both immunoglobulin M and i...

Evaluating Efficiency of a Provincial Telerehabilitation Service in Improving Access to Care During the COVID-19 Pandemic.

SCOPE: Early in the COVID-19 pandemic, community rehabilitation stakeholders from a provincial health system designed a novel telerehabilitation servi...

Large-scale electrophysiology and deep learning reveal distorted neural signal dynamics after hearing loss.

Listeners with hearing loss often struggle to understand speech in noise, even with a hearing aid. To better understand the auditory processing defici...

In-Sensor Artificial Intelligence and Fusion With Electronic Medical Records for At-Home Monitoring.

This work presents an artificial intelligence (AI) framework for real-time, personalized sepsis prediction four hours before onset through fusion of e...

A genetic programming-based convolutional deep learning algorithm for identifying COVID-19 cases via X-ray images.

Evolutionary algorithms have been successfully employed to find the best structure for many learning algorithms including neural networks. Due to thei...

Deep learning approach for early prediction of COVID-19 mortality using chest X-ray and electronic health records.

BACKGROUND: An artificial-intelligence (AI) model for predicting the prognosis or mortality of coronavirus disease 2019 (COVID-19) patients will allow...

Is ultrasound-guided hip aspiration more successful than fluoroscopic-guided aspiration in diagnosing prosthetic joint infection?

: aspiration of total hip arthroplasty (THA) is commonly performed to assist in the diagnosis of prosthetic joint infection (PJI). This study aimed to...

2D medical image synthesis using transformer-based denoising diffusion probabilistic model.

. Artificial intelligence (AI) methods have gained popularity in medical imaging research. The size and scope of the training image datasets needed fo...

BacterAI maps microbial metabolism without prior knowledge.

Training artificial intelligence (AI) systems to perform autonomous experiments would vastly increase the throughput of microbiology; however, few mic...

A dosing strategy model of deep deterministic policy gradient algorithm for sepsis patients.

BACKGROUND: A growing body of research suggests that the use of computerized decision support systems can better guide disease treatment and reduce th...

Artificial intelligence-based computer aided detection (AI-CAD) in the fight against tuberculosis: Effects of moving health technologies in global health.

Computer Aided Detection software based on Artificial Intelligence (AI-CAD), combined with chest X-rays have recently been promoted as an easy fix for...

Bio-SHARPE: Bioinspired Soft and High Aspect Ratio Pumping Element for Robotic and Medical Applications.

The advent of soft robots has solved many issues posed by their rigid counterparts, including safer interactions with humans and the capability to wor...

Comparative study of lipid nanoparticle-based mRNA vaccine bioprocess with machine learning and combinatorial artificial neural network-design of experiment approach.

To develop a combinatorial artificial-neural-network design-of-experiment (ANN-DOE) model, the effect of ionizable lipid, an ionizable lipid-to-choles...

Generating and Weighting Semantically Consistent Sample Pairs for Ultrasound Contrastive Learning.

Well-annotated medical datasets enable deep neural networks (DNNs) to gain strong power in extracting lesion-related features. Building such large and...

A deep learning-based application for COVID-19 diagnosis on CT: The Imaging COVID-19 AI initiative.

BACKGROUND: Recently, artificial intelligence (AI)-based applications for chest imaging have emerged as potential tools to assist clinicians in the di...

Prediction of atmospheric pollutants in urban environment based on coupled deep learning model and sensitivity analysis.

Accurate and efficient predictions of pollutants in the atmosphere provide a reliable basis for the scientific management of atmospheric pollution. Th...

AI-Driven De Novo Design and Molecular Modeling for Discovery of Small-Molecule Compounds as Potential Drug Candidates Targeting SARS-CoV-2 Main Protease.

Over the past three years, significant progress has been made in the development of novel promising drug candidates against COVID-19. However, SARS-Co...