Public Health

A multistage multimodal deep learning model for disease severity assessment and early warnings of high-risk patients of COVID-19.

The outbreak of coronavirus disease 2019 (COVID-19) has caused massive infections and large death tolls worldwide. Despite many studies on the clinical characteristics and the treatment plans of COVID-19, they rarely conduct in-depth prognostic research on leveraging consecutive rounds of multimodal clinical examination and laboratory test data to facilitate clinical decision-making for the treatm...

Mapping the plague through natural language processing.

Pandemic diseases such as plague have produced a vast amount of literature providing information about the spatiotemporal extent, transmission, or countermeasures. However, the manual extraction of such information from running text is a tedious process, and much of this information remains locked into a narrative format. Natural Language processing (NLP) is a promising tool for the automated extr...

Validating administrative data to identify complex surgical site infections following cardiac implantable electronic device implantation: a comparison of traditional methods and machine learning.

BACKGROUND: Cardiac implantable electronic device (CIED) surgical site infections (SSIs) have been outpacing the increases in implantation of these de...

Pharmacological, Non-Pharmacological Policies and Mutation: An Artificial Intelligence Based Multi-Dimensional Policy Making Algorithm for Controlling the Casualties of the Pandemic Diseases.

Fighting against the pandemic diseases with unique characters requires new sophisticated approaches like the artificial intelligence. This paper devel...

Socially Assistive Humanoid Robots: Effects on Depression and Health-Related Quality of Life among Low-Income, Socially Isolated Older Adults in South Korea.

Using a mixed-method study design, we examined the effects of a socially assistive humanoid robot (SAHR), called Hyodol, on depressive symptoms and he...

A CNN-transformer fusion network for COVID-19 CXR image classification.

The global health crisis due to the fast spread of coronavirus disease (Covid-19) has caused great danger to all aspects of healthcare, economy, and o...

Public sentiment on the global outbreak of monkeypox: an unsupervised machine learning analysis of 352,182 twitter posts.

OBJECTIVES: This study aimed to study the public's sentiments on the current monkeypox outbreaks via an unsupervised machine learning analysis of soci...

Real-Time Ship Segmentation in Maritime Surveillance Videos Using Automatically Annotated Synthetic Datasets.

This work proposes a new system capable of real-time ship instance segmentation during maritime surveillance missions by unmanned aerial vehicles usin...

Forecasting Weekly Dengue Cases by Integrating Google Earth Engine-Based Risk Predictor Generation and Google Colab-Based Deep Learning Modeling in Fortaleza and the Federal District, Brazil.

Efficient and accurate dengue risk prediction is an important basis for dengue prevention and control, which faces challenges, such as downloading and...

Nondestructive and multiplex differentiation of pathogenic microorganisms from spoilage microflora on seafood using paper chromogenic array and neural network.

Non-destructive detection of human foodborne pathogens is critical to ensuring food safety and public health. Here, we report a new method using a pap...

A deep learning approach to real-time HIV outbreak detection using genetic data.

Pathogen genomic sequence data are increasingly made available for epidemiological monitoring. A main interest is to identify and assess the potential...

Automated Diagnosis of COVID-19 Using Deep Supervised Autoencoder With Multi-View Features From CT Images.

Accurate and rapid diagnosis of coronavirus disease 2019 (COVID-19) from chest CT scans is of great importance and urgency during the worldwide outbre...

A Two-Mode Underwater Smart Sensor Object for Precision Aquaculture Based on AIoT Technology.

Monitoring the status of culture fish is an essential task for precision aquaculture using a smart underwater imaging device as a non-intrusive way of...

Identification of blood species based on surface-enhanced Raman scattering spectroscopy and convolutional neural network.

The identification of blood species is of great significance in many aspects such as forensic science, wildlife protection, and customs security and q...

Deep learning techniques for detecting and recognizing face masks: A survey.

The year 2020 brought many changes to the lives of people all over the world with the outbreak of COVID-19; we saw lockdowns for months and deaths of ...

Recognition and segmentation of individual pigs based on Swin Transformer.

Recognition of individual pigs is critical to the monitoring of pig body size and physiological health status in large-scale pig farms. In this study,...

Verbal Autopsy as a Tool for Defining Causes of Death in Specific Healthcare Contexts: Study of Applicability through a Traditional Literature Review.

Autopsy examination, the gold standard for defining causes of death, is often difficult to apply in certain health care settings, especially in develo...

Multimodal biomedical AI.

The increasing availability of biomedical data from large biobanks, electronic health records, medical imaging, wearable and ambient biosensors, and t...

A Natural Language Processing (NLP) Evaluation on COVID-19 Rumour Dataset Using Deep Learning Techniques.

: Since December 2019, the coronavirus (COVID-19) epidemic has sparked considerable alarm among the general community and significantly affected socie...

Comments on "Identifying psychological antecedents and predictors of vaccine hesitancy through machine learning: A cross sectional study among chronic disease patients of deprived urban neighbourhood, India".

Dear Editor, we read the publication by Rustagi et al. "Identifying psychological antecedents and predictors of vaccine hesitancy through machine lear...