Infectious Disease

Explainable artificial intelligence model for identifying COVID-19 gene biomarkers.

AIM: COVID-19 has revealed the need for fast and reliable methods to assist clinicians in diagnosing the disease. This article presents a model that applies explainable artificial intelligence (XAI) methods based on machine learning techniques on COVID-19 metagenomic next-generation sequencing (mNGS) samples.

Deep Learning-Based Bioactive Therapeutic Peptide Generation and Screening.

Many bioactive peptides demonstrated therapeutic effects over complicated diseases, such as antiviral, antibacterial, anticancer, . It is possible to generate a large number of potentially bioactive peptides using deep learning in a manner analogous to the generation of chemical compounds using the acquired bioactive peptides as a training set. Such generative techniques would be significant for ...

Using Haplotype-Based Artificial Intelligence to Evaluate SARS-CoV-2 Novel Variants and Mutations.

IMPORTANCE: Earlier detection of emerging novel SARS-COV-2 variants is important for public health surveillance of potential viral threats and for ear...

PneuNet: deep learning for COVID-19 pneumonia diagnosis on chest X-ray image analysis using Vision Transformer.

A long-standing challenge in pneumonia diagnosis is recognizing the pathological lung texture, especially the ground-glass appearance pathological tex...

Machine learning assisted hepta band THz metamaterial absorber for biomedical applications.

A hepta-band terahertz metamaterial absorber (MMA) with modified dual T-shaped resonators deposited on polyimide is presented for sensing applications...

Malaria Detection Using Advanced Deep Learning Architecture.

Malaria is a life-threatening disease caused by parasites that are transmitted to humans through the bites of infected mosquitoes. The early diagnosis...

Artificial Intelligence in Paediatric Tuberculosis.

Tuberculosis (TB) continues to be a leading cause of death in children despite global efforts focused on early diagnosis and interventions to limit th...

A survey of machine learning-based methods for COVID-19 medical image analysis.

The ongoing COVID-19 pandemic caused by the SARS-CoV-2 virus has already resulted in 6.6 million deaths with more than 637 million people infected aft...

Explainable deep learning model to predict invasive bacterial infection in febrile young infants: A retrospective study.

BACKGROUND: Machine learning models have demonstrated superior performance in predicting invasive bacterial infection (IBI) in febrile infants compare...

Compressed Sensing Data with Performing Audio Signal Reconstruction for the Intelligent Classification of Chronic Respiratory Diseases.

Chronic obstructive pulmonary disease (COPD) concerns the serious decline of human lung functions. These have emerged as one of the most concerning he...

A hybrid intelligent model for early validation of infectious diseases: An explorative study of machine learning approaches.

Literature reports several infectious diseases news validation approaches, but none is economically effective for collecting and classifying informati...

Entity and relation extraction from clinical case reports of COVID-19: a natural language processing approach.

BACKGROUND: Extracting relevant information about infectious diseases is an essential task. However, a significant obstacle in supporting public healt...

CNN-RNN Network Integration for the Diagnosis of COVID-19 Using Chest X-ray and CT Images.

The 2019 coronavirus disease (COVID-19) has rapidly spread across the globe. It is crucial to identify positive cases as rapidly as humanely possible ...

Deep learning identified genetic variants for COVID-19-related mortality among 28,097 affected cases in UK Biobank.

Analysis of host genetic components provides insights into the susceptibility and response to viral infection such as severe acute respiratory syndrom...

Implementing deep learning models for the classification of Echinococcus multilocularis infection in human liver tissue.

BACKGROUND: The histological diagnosis of alveolar echinococcosis can be challenging. Decision support models based on deep learning (DL) are increasi...

Classification of COVID-19 from community-acquired pneumonia: Boosting the performance with capsule network and maximum intensity projection image of CT scans.

BACKGROUND: The coronavirus disease 2019 (COVID-19) and community-acquired pneumonia (CAP) present a high degree of similarity in chest computed tomog...

Do artificial neural networks love sex? How the combination of artificial neural networks with evolutionary algorithms may help to identify gender influence in rheumatic diseases.

Although medical research has been performed predominantly on men both in preclinical and clinical studies, continuous efforts have been made to overc...

COVID-19 Classification on Chest X-ray Images Using Deep Learning Methods.

Since December 2019, the coronavirus disease has significantly affected millions of people. Given the effect this disease has on the pulmonary systems...

Comparison of the Diagnostic Performance of Deep Learning Algorithms for Reducing the Time Required for COVID-19 RT-PCR Testing.

(1) Background: Rapid and accurate negative discrimination enables efficient management of scarce isolated bed resources and adequate patient accommod...

Racial Health Disparities and Black Heterogeneity in COVID-19: A Case Study of Miami Gardens.

The COVID-19 pandemic is a critical public health concern that has disproportionately affected the Black community in the United States. The purpose o...