Infectious Disease

Automated prediction of COVID-19 severity upon admission by chest X-ray images and clinical metadata aiming at accuracy and explainability.

In the past few years COVID-19 posed a huge threat to healthcare systems around the world. One of the first waves of the pandemic hit Northern Italy severely resulting in high casualties and in the near breakdown of primary care. Due to these facts, the Covid CXR Hackathon-Artificial Intelligence for Covid-19 prognosis: aiming at accuracy and explainability challenge had been launched at the begin...

Deep Survival Analysis With Clinical Variables for COVID-19.

OBJECTIVE: Millions of people have been affected by coronavirus disease 2019 (COVID-19), which has caused millions of deaths around the world. Artificial intelligence (AI) plays an increasing role in all areas of patient care, including prognostics. This paper proposes a novel predictive model based on one dimensional convolutional neural networks (1D CNN) to use clinical variables in predicting t...

Implementation of deep learning artificial intelligence in vision-threatening disease screenings for an underserved community during COVID-19.

INTRODUCTION: Age-related macular degeneration, diabetic retinopathy, and glaucoma are vision-threatening diseases that are leading causes of vision l...

[Robotic esophageal surgery].

Robot-assisted minimally invasive esophagectomy (RAMIE) is increasingly becoming established as a standard procedure in surgical centers for esophagec...

Bacteria-Specific Feature Selection for Enhanced Antimicrobial Peptide Activity Predictions Using Machine-Learning Methods.

There are several classes of short peptide molecules, known as antimicrobial peptides (AMPs), which are produced during the immune responses of living...

The predictive model for COVID-19 pandemic plastic pollution by using deep learning method.

Pandemic plastics (e.g., masks, gloves, aprons, and sanitizer bottles) are global consequences of COVID-19 pandemic-infected waste, which has increase...

Benchmarking machine learning robustness in Covid-19 genome sequence classification.

The rapid spread of the COVID-19 pandemic has resulted in an unprecedented amount of sequence data of the SARS-CoV-2 genome-millions of sequences and ...

Deep learning models for hepatitis E incidence prediction leveraging meteorological factors.

BACKGROUND: Infectious diseases are a major threat to public health, causing serious medical consumption and casualties. Accurate prediction of infect...

DeepDetect: Deep Learning of Peptide Detectability Enhanced by Peptide Digestibility and Its Application to DIA Library Reduction.

In tandem mass spectrometry-based proteomics, proteins are digested into peptides by specific protease(s), but generally only a fraction of peptides c...

Identification of medicinal plant-based phytochemicals as a potential inhibitor for SARS-CoV-2 main protease (M) using molecular docking and deep learning methods.

Highly transmissive and rapidly evolving Coronavirus disease-2019 (COVID-19), a viral disease caused by severe acute respiratory syndrome coronavirus ...

New proposal of viral genome representation applied in the classification of SARS-CoV-2 with deep learning.

BACKGROUND: In December 2019, the first case of COVID-19 was described in Wuhan, China, and by July 2022, there were already 540 million confirmed cas...

A hybrid deep learning approach for COVID-19 detection based on genomic image processing techniques.

The coronavirus disease 2019 (COVID-19) pandemic has been spreading quickly, threatening the public health system. Consequently, positive COVID-19 cas...

COVID-19 imaging, where do we go from here? Bibliometric analysis of medical imaging in COVID-19.

OBJECTIVES: We conducted a systematic and comprehensive bibliometric analysis of COVID-19-related medical imaging to determine the current status and ...

Measurement and Processing of Thermographic Data of Passing Persons for Epidemiological Purposes.

Non-contact temperature measurement of persons during an epidemic is the most preferred measurement option because of the safety of personnel and mini...

Comprehensive Functional Annotation of Metagenomes and Microbial Genomes Using a Deep Learning-Based Method.

Comprehensive protein function annotation is essential for understanding microbiome-related disease mechanisms in the host organisms. However, a large...

Natural language processing in radiology: Clinical applications and future directions.

Natural language processing (NLP) is a wide range of techniques that allows computers to interact with human text. Applications of NLP in everyday lif...

Assessment of Helicobacter pylori infection by deep learning based on endoscopic videos in real time.

BACKGROUND AND AIMS: Endoscopic assessment of Helicobacter pylori infection is a simple and effective method. Here, we aimed to develop a deep learnin...

Socially Assistive Robots for People Living with Dementia in Long-Term Facilities: A Systematic Review and Meta-Analysis of Randomized Controlled Trials.

BACKGROUND AND OBJECTIVE: The purpose of our study was to explore the immediate and long-term effects of socially assistive robots (SARs) on neuropsyc...

Computed tomography-based COVID-19 triage through a deep neural network using mask-weighted global average pooling.

BACKGROUND: There is an urgent need to find an effective and accurate method for triaging coronavirus disease 2019 (COVID-19) patients from millions o...

Biases associated with database structure for COVID-19 detection in X-ray images.

Several artificial intelligence algorithms have been developed for COVID-19-related topics. One that has been common is the COVID-19 diagnosis using c...