Flu & URI

Lexicon-based sentiment analysis to detect opinions and attitude towards COVID-19 vaccines on Twitter in Italy.

The paper proposes a methodology based on Natural Language Processing (NLP) and Sentiment Analysis (SA) to get insights into sentiments and opinions toward COVID-19 vaccination in Italy. The studied dataset consists of vaccine-related tweets published in Italy from January 2021 to February 2022. In the considered period, 353,217 tweets have been analyzed, obtained after filtering 1,602,940 tweets ...

Leveraging deep learning to improve vaccine design.

Deep learning has led to incredible breakthroughs in areas of research, from self-driving vehicles to solutions, to formal mathematical proofs. In the biomedical sciences, however, the revolutionary results seen in other fields are only now beginning to be realized. Vaccine research and development efforts represent an application with high public health significance. Protein structure prediction,...

Successful all robotic-assisted excision of highly malignant mediastinal neuroblastoma in a toddler: A case report.

An otherwise well 28-month-old girl presented with fever/left thigh pain. Computed tomography identified a 7 cm right posterior mediastinal tumor exte...

A Deep Learning Approach for Dengue Fever Prediction in Malaysia Using LSTM with Spatial Attention.

This research aims to predict dengue fever cases in Malaysia using machine learning techniques. A dataset consisting of weekly dengue cases at the sta...

MSCCov19Net: multi-branch deep learning model for COVID-19 detection from cough sounds.

Coronavirus has an impact on millions of lives and has been added to the important pandemics that continue to affect with its variants. Since it is tr...

Deep reinforcement learning-based pairwise DNA sequence alignment method compatible with embedded edge devices.

Sequence alignment is an essential component of bioinformatics, for identifying regions of similarity that may indicate functional, structural, or evo...

Deep-Learning Model for Influenza Prediction From Multisource Heterogeneous Data in a Megacity: Model Development and Evaluation.

BACKGROUND: In megacities, there is an urgent need to establish more sensitive forecasting and early warning methods for acute respiratory infectious ...

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...

An artificial intelligence algorithm-based smartphone application for daily cough monitoring.

Examining the Use of an Artificial Intelligence Model to Diagnose Influenza: Development and Validation Study.

BACKGROUND: The global burden of influenza is substantial. It is a major disease that causes annual epidemics and occasionally, pandemics. Given that ...

Virus Detection and Identification in Minutes Using Single-Particle Imaging and Deep Learning.

The increasing frequency and magnitude of viral outbreaks in recent decades, epitomized by the COVID-19 pandemic, has resulted in an urgent need for r...

Molecular modeling of C1-inhibitor as SARS-CoV-2 target identified from the immune signatures of multiple tissues: An integrated bioinformatics study.

The expeditious transmission of the severe acute respiratory coronavirus 2 (SARS-CoV-2), a strain of COVID-19, crumbled the global economic strength a...

Predicting Antigenic Distance from Genetic Data for PRRSV-Type 1: Applications of Machine Learning.

The control of porcine reproductive and respiratory syndrome (PRRS) remains a significant challenge due to the genetic and antigenic variability of th...

Considerations and Challenges for Real-World Deployment of an Acoustic-Based COVID-19 Screening System.

Coronavirus disease 2019 (COVID-19) has led to countless deaths and widespread global disruptions. Acoustic-based artificial intelligence (AI) tools c...

An automated, fully-integrated nucleic acid analyzer based on microfluidic liquid handling robot technique.

On-site nucleic acid testing (NAT) plays an important role for disease monitoring and pathogen diagnosis. In this work, we developed an automated and ...

Integrative transcriptome analysis of SARS-CoV-2 human-infected cells combined with deep learning algorithms identifies two potential cellular targets for the treatment of coronavirus disease.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) quickly spread worldwide, leading coronavirus disease 2019 (COVID-19) to hit pandemic lev...

Predicting risk of sepsis, comparison between machine learning methods: a case study of a Virginia hospital.

Sepsis is an inflammation caused by the body's systemic response to an infection. The infection could be a result of many diseases, such as pneumonia,...

Automation of generative adversarial network-based synthetic data-augmentation for maximizing the diagnostic performance with paranasal imaging.

Thus far, there have been no reported specific rules for systematically determining the appropriate augmented sample size to optimize model performanc...

A wearable soft robot that can alleviate the pain and fear of the wearer.

Social soft robotics may provide a new solution for alleviating human pain and fear. Here, we introduce a hand-held soft robot that can be clenched by...

Phenotyping in clinical text with unsupervised numerical reasoning for patient stratification.

Phenotypic information of patients, as expressed in clinical text, is important in many clinical applications such as identifying patients at risk of ...