Infectious Disease

AI-Based Quantitative CT Analysis of Temporal Changes According to Disease Severity in COVID-19 Pneumonia.

OBJECTIVE: To quantitatively evaluate computed tomography (CT) parameters of coronavirus disease 2019 (COVID-19) pneumonia an artificial intelligence (AI)-based software in different clinical severity groups during the disease course.

[Chest radiological lesions in COVID-19 : from classical imaging to artificial intelligence].

In the course of the pandemic induced by the appearance of a new coronavirus (SARS-CoV-2; COVID-19) causing acute respiratory distress syndrome (ARDS), we had to rethink the diagnostic approach for patients suffering from respiratory symptoms. Indeed, although the use of RT-PCR remains the keystone of the diagnosis, the delay in diagnosis as well as the overload of the microbiological platforms ha...

Application of bacteria-mediated gene therapy in tumor treatment.

INTRODUCTION: Gene therapy refers to the use of vectors to introduce target genes into target cells to exert a therapeutic effect on tumors. As a new ...

In Silico Prediction and Validation of LmGt Inhibitors Using QSAR and Molecular Docking Approaches

Leishmaniasis caused by Leishmania mexicana relies on Leishmania mexicana gluscose transporter (LmGT) receptors, which play an important role in glu...

Two-Stage Automatic Liver Classification System Based on Deep Learning Approach Using CT Images.

Alveolar echinococcosis (AE) is a parasitic disease caused by Echinococcus multilocularis, where early detection is crucial for effective treatment. T...

A novel sensor array combined with machine learning for the effective differentiation of multiple classes of antibiotics based on copper-based nanozymes with laccase-like activity.

A nanozyme sensor array was developed combining with machine learning algorithms for the effective identification and differentiation of multiple anti...

Machine learning based prediction by PlantCdMiner and experimental validation of cadmium-responsive genes in plants.

Plants have evolved diverse adaptive mechanisms to sense and respond to environmental stimuli such as cadmium stress. The regulation of gene expressio...

Prognostic Value of the Brixia Radiological Score in COVID-19 Patients: A Retrospective Study from Romania.

The novel coronavirus pandemic, SARS-CoV-2, has a variable clinical spectrum, ranging from asymptomatic to critical forms. High mortality and morbidit...

A deep learning and molecular modeling approach to repurposing Cangrelor as a potential inhibitor of Nipah virus.

Deforestation, urbanization, and climate change have significantly increased the risk of zoonotic diseases. Nipah virus (NiV) of Paramyxoviridae famil...

KNDM: A Knowledge Graph Transformer and Node Category Sensitive Contrastive Learning Model for Drug and Microbe Association Prediction.

It has been proven that the microbiome in human bodies can promote or inhibit the treatment effects of the drugs by affecting their toxicities and act...

Integrating different approaches for the identification of new disruptors of HIV-1 capsid multimerization.

Human Immunodeficiency Virus (HIV) belongs to the Lentivirus genus, Retroviridae family, enveloped by a lipid bilayer within which the capsid protein ...

Mitigating Bias in Machine Learning Models with Ethics-Based Initiatives: The Case of Sepsis.

This paper discusses ethics-based strategies for mitigating bias in machine learning models used to predict sepsis onset. The first part discusses how...

Use of Artificial Intelligence in Current Fight Against Antimicrobial Resistance.

Antimicrobial resistance (AMR) poses a significant global health threat, with projections indicating it could surpass cancer in mortality rates by 205...

Stigma Attitudes Toward HIV/AIDS From 2011 Through 2023 in Japan: Retrospective Study in Japan.

BACKGROUND: Stigma associated with HIV/AIDS continues to be a major barrier to prevention, management, and care. HIV stigma can negatively influence h...

IFPTML Multi-Output Model for Anti-Retroviral Compounds Including the Drug Structure and Target Protein Sequence Information.

Retroviruses such as HIV cause significant diseases in humans and other organisms, making the discovery of antiretroviral (ARV) drugs a critical prior...

Promptable segmentation of CT lung lesions based on improved U-Net and Segment Anything model (SAM).

BackgroundComputed tomography (CT) is widely used in clinical diagnosis of lung diseases. The automatic segmentation of lesions in CT images aids in t...

Prescriptive analytics decision-making system for cardiovascular disease prediction in long COVID patients using advanced reinforcement learning algorithms.

In recent years Covid-19 impact is causing unprecedented difficulties worldwide, affecting lifestyle choices. The post-pandemic era has made this even...

Application of in-silico approaches in subunit vaccines: Overcoming the challenges of antigen and adjuvant development.

Subunit vaccines are crucial in preventing modern diseases due to their safety, stability, and ability to elicit targeted immune responses. However, c...

Electrocardiographic diagnostic possibilities for atrial fibrillation using artificial intelligence: Differentiation from sinus rhythm and other arrhythmias with the PMcardio app in COVID-19 patients.

BACKGROUND: Artificial intelligence (AI) has shown potential in enhancing ECG analysis, but its accuracy in detecting atrial fibrillation (AF) in COVI...

The Accuracy of ChatGPT-4o in Interpreting Chest and Abdominal X-Ray Images.

Large language models (LLMs), such as ChatGPT, have emerged as potential clinical support tools to enhance precision in personalized patient care, bu...