Flu & URI

At-admission prediction of mortality and pulmonary embolism in an international cohort of hospitalised patients with COVID-19 using statistical and machine learning methods.

By September 2022, more than 600 million cases of SARS-CoV-2 infection have been reported globally, resulting in over 6.5 million deaths. COVID-19 mortality risk estimators are often, however, developed with small unrepresentative samples and with methodological limitations. It is highly important to develop predictive tools for pulmonary embolism (PE) in COVID-19 patients as one of the most sever...

Leveraging artificial intelligence in vaccine development: A narrative review.

Vaccine development stands as a cornerstone of public health efforts, pivotal in curbing infectious diseases and reducing global morbidity and mortality. However, traditional vaccine development methods are often time-consuming, costly, and inefficient. The advent of artificial intelligence (AI) has ushered in a new era in vaccine design, offering unprecedented opportunities to expedite the proces...

Model based on the automated AI-driven CT quantification is effective for the diagnosis of refractory Mycoplasma pneumoniae pneumonia.

The prediction of refractory Mycoplasma pneumoniae pneumonia (RMPP) remains a clinically significant challenge. This study aimed to develop an early p...

Automatic wild bird repellent system that is based on deep-learning-based wild bird detection and integrated with a laser rotation mechanism.

Wild bird repulsion is critical in agriculture because it helps avoid agricultural food losses and mitigates the risk of avian influenza. Wild birds t...

Vaccine design and development: Exploring the interface with computational biology and AI.

Computational biology involves applying computer science and informatics techniques in biology to understand complex biological data. It allows us to ...

Factors of acute respiratory infection among under-five children across sub-Saharan African countries using machine learning approaches.

Symptoms of Acute Respiratory infections (ARIs) among under-five children are a global health challenge. We aimed to train and evaluate ten machine le...

Virtual resonance: analyzing IPA usage intensity under COVID-19's isolating canopy.

The widespread adoption of smartphones coupled with advancements in artificial intelligence has significantly propelled the use of intelligent persona...

Modeling and control of COVID-19 disease using deep reinforcement learning method.

The prevalence of epidemics has been studied by researchers in various fields. In the last 2 years, the outbreak of COVID-19 has affected the health, ...

Empowering standardization of cancer vaccines through ontology: enhanced modeling and data analysis.

BACKGROUND: The exploration of cancer vaccines has yielded a multitude of studies, resulting in a diverse collection of information. The heterogeneity...

Assessing the quality of artificial intelligence-generated patient counseling for rhinosinusitis.

GPT-4 generated moderate quality information in response to questions regarding sinusitis and surgery. GPT-4 generated significantly higher quality re...

A Paper-Based Multiplexed Serological Test to Monitor Immunity against SARS-COV-2 Using Machine Learning.

The rapid spread of SARS-CoV-2 caused the COVID-19 pandemic and accelerated vaccine development to prevent the spread of the virus and control the dis...

Exploratory mapping of tumor associated macrophage nanoparticle article abstracts using an eLDA topic modeling machine learning approach.

The role of macrophages in regulating the tumor microenvironment has spurned the exponential generation of nanoparticle targeting technologies. With t...

A versatile automated pipeline for quantifying virus infectivity by label-free light microscopy and artificial intelligence.

Virus infectivity is traditionally determined by endpoint titration in cell cultures, and requires complex processing steps and human annotation. Here...

A Machine Learning Approach to Identify Key Residues Involved in Protein-Protein Interactions Exemplified with SARS-CoV-2 Variants.

Human infection with the coronavirus disease 2019 (COVID-19) is mediated by the binding of the spike protein of the severe acute respiratory syndrome ...

Emergence of artificial intelligence for automating cone-beam computed tomography-derived maxillary sinus imaging tasks. A systematic review.

Cone-beam computed tomography (CBCT) imaging of the maxillary sinus is indispensable for implantologists, offering three-dimensional anatomical visual...

Utilization of machine learning for dengue case screening.

Dengue causes approximately 10.000 deaths and 100 million symptomatic infections annually worldwide, making it a significant public health concern. To...

Efficient deep learning-based approach for malaria detection using red blood cell smears.

Malaria is an extremely malignant disease and is caused by the bites of infected female mosquitoes. This disease is not only infectious among humans, ...

Preliminary study on AI-assisted diagnosis of bone remodeling in chronic maxillary sinusitis.

OBJECTIVE: To construct the deep learning convolution neural network (CNN) model and machine learning support vector machine (SVM) model of bone remod...

Machine learning prediction of malaria vaccine efficacy based on antibody profiles.

Immunization through repeated direct venous inoculation of Plasmodium falciparum (Pf) sporozoites (PfSPZ) under chloroquine chemoprophylaxis, using th...

Mathematical analysis and prediction of future outbreak of dengue on time-varying contact rate using machine learning approach.

This article introduces a novel mathematical model analyzing the dynamics of Dengue in the recent past, specifically focusing on the 2023 outbreak of ...