Infectious Disease

Deep learning for deterioration prediction of COVID-19 patients based on time-series of three vital signs.

Unrecognized deterioration of COVID-19 patients can lead to high morbidity and mortality. Most existing deterioration prediction models require a large number of clinical information, typically collected in hospital settings, such as medical images or comprehensive laboratory tests. This is infeasible for telehealth solutions and highlights a gap in deterioration prediction models based on minimal...

Artificial intelligence-driven prediction of COVID-19-related hospitalization and death: a systematic review.

AIM: To perform a systematic review on the use of Artificial Intelligence (AI) techniques for predicting COVID-19 hospitalization and mortality using primary and secondary data sources.

The Rise of AI: How Artificial Intelligence is Revolutionizing Infectious Disease Control.

Artificial Intelligence (AI) has proven to be an effective tool in predicting, detecting, and mitigating the spread of infectious diseases, especially...

Pathological changes or technical artefacts? The problem of the heterogenous databases in COVID-19 CXR image analysis.

BACKGROUND: When the COVID-19 pandemic commenced in 2020, scientists assisted medical specialists with diagnostic algorithm development. One scientifi...

Diagnosis of invasive fungal infections: challenges and recent developments.

BACKGROUND: The global burden of invasive fungal infections (IFIs) has shown an upsurge in recent years due to the higher load of immunocompromised pa...

Evolving a Pipeline Approach for Abstract Meaning Representation Parsing Towards Dynamic Neural Networks.

Meaning Representation parsing aims to represent a sentence as a structured, Directed, Acyclic Graph (DAG), in an attempt to extract meaning from text...

COV-MobNets: a mobile networks ensemble model for diagnosis of COVID-19 based on chest X-ray images.

BACKGROUND: The medical profession is facing an excessive workload, which has led to the development of various Computer-Aided Diagnosis (CAD) systems...

Modification of a Conventional Deep Learning Model to Classify Simulated Breathing Patterns: A Step toward Real-Time Monitoring of Patients with Respiratory Infectious Diseases.

The emergence of the global coronavirus pandemic in 2019 (COVID-19 disease) created a need for remote methods to detect and continuously monitor patie...

PeakDetective: A Semisupervised Deep Learning-Based Approach for Peak Curation in Untargeted Metabolomics.

Peak-detection algorithms currently used to process untargeted metabolomics data were designed to maximize sensitivity at the sacrifice of selectively...

Predicting the antigenic evolution of SARS-COV-2 with deep learning.

The relentless evolution of SARS-CoV-2 poses a significant threat to public health, as it adapts to immune pressure from vaccines and natural infectio...

Discovery of senolytics using machine learning.

Cellular senescence is a stress response involved in ageing and diverse disease processes including cancer, type-2 diabetes, osteoarthritis and viral ...

HLA-II immunopeptidome profiling and deep learning reveal features of antigenicity to inform antigen discovery.

CD4+ T cell responses are exquisitely antigen specific and directed toward peptide epitopes displayed by human leukocyte antigen class II (HLA-II) on ...

Improve the performance of CT-based pneumonia classification via source data reweighting.

Pneumonia is a life-threatening disease. Computer tomography (CT) imaging is broadly used for diagnosing pneumonia. To assist radiologists in accurate...

Performance of an automated deep learning algorithm to identify hepatic steatosis within noncontrast computed tomography scans among people with and without HIV.

PURPOSE: Hepatic steatosis (fatty liver disease) affects 25% of the world's population, particularly people with HIV (PWH). Pharmacoepidemiologic stud...

Rule ensemble method with adaptive group lasso for heterogeneous treatment effect estimation.

The increasing scientific attention given to precision medicine based on real-world data has led to many recent studies clarifying the relationships b...

Misinformation and Public Health Messaging in the Early Stages of the Mpox Outbreak: Mapping the Twitter Narrative With Deep Learning.

BACKGROUND: Shortly after the worst of the COVID-19 pandemic, an outbreak of mpox introduced another critical public health emergency. Like the COVID-...

Leveraging human expert image annotations to improve pneumonia differentiation through human knowledge distillation.

In medical imaging, deep learning models can be a critical tool to shorten time-to-diagnosis and support specialized medical staff in clinical decisio...

A deep learning predictive model for public health concerns and hesitancy toward the COVID-19 vaccines.

Throughout the pandemic era, COVID-19 was one of the remarkable unexpected situations over the past few years, but with the decentralization and globa...

Explainable COVID-19 Detection Based on Chest X-rays Using an End-to-End RegNet Architecture.

COVID-19,which is caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is one of the worst pandemics in recent history. The ide...

Robot-Guided Stereotactic Puncture and Drainage in the Treatment of Thalamic Abscess.

Brain abscess is rare in clinic, the reported incidence is only 0.4 to 0.90 per 100,000 population, and most of them have a history of prodromal infec...