Public Health & Policy

Fall-from-Height Detection Using Deep Learning Based on IMU Sensor Data for Accident Prevention at Construction Sites.

Workers at construction sites are prone to fall-from-height (FFH) accidents. The severity of injury can be represented by the acceleration peak value. In the study, a risk prediction against FFH was made using IMU sensor data for accident prevention at construction sites. Fifteen general working movements (NF: non-fall), five low-hazard-fall movements, (LF), and five high-hazard-FFH movements (HF)...

Food traceability 4.0 as part of the fourth industrial revolution: key enabling technologies.

Food Traceability 4.0 (FT 4.0) is about tracing foods in the era of the fourth industrial revolution (Industry 4.0) with techniques and technologies reflecting this new revolution. Interest in food traceability has gained momentum in response to, among others events, the outbreak of the COVID-19 pandemic, reinforcing the need for digital food traceability that prevents food fraud and provides reli...

An End-to-End Human Abnormal Behavior Recognition Framework for Crowds With Mentally Disordered Individuals.

Abnormal or violent behavior by people with mental disorders is common. When individuals with mental disorders exhibit abnormal behavior in public pla...

DAFLNet: Dual Asymmetric Feature Learning Network for COVID-19 Disease Diagnosis in X-Rays.

COVID-19 has become the largest public health event worldwide since its outbreak, and early detection is a prerequisite for effective treatment. Chest...

An Empirical Analysis of an Optimized Pretrained Deep Learning Model for COVID-19 Diagnosis.

As a result of the COVID-19 outbreak, which has put the world in an unprecedented predicament, thousands of people have died. Data from structured and...

Analysis of epidemiological association patterns of serum thyrotropin by combining random forests and Bayesian networks.

BACKGROUND: Approaching epidemiological data with flexible machine learning algorithms is of great value for understanding disease-specific associatio...

Classification and Reconstruction of Biomedical Signals Based on Convolutional Neural Network.

The efficient biological signal processing method can effectively improve the efficiency of researchers to explore the work of life mechanism, so as t...

Convolutional Neural Networks and Heuristic Methods for Crowd Counting: A Systematic Review.

The crowd counting task has become a pillar for crowd control as it provides information concerning the number of people in a scene. It is helpful in ...

InjectMeAI-Software Module of an Autonomous Injection Humanoid.

The recent pandemic outbreak proved social distancing effective in helping curb the spread of SARS-CoV-2 variants along with the wearing of masks and ...

Human Gait Analysis: A Sequential Framework of Lightweight Deep Learning and Improved Moth-Flame Optimization Algorithm.

Human gait recognition has emerged as a branch of biometric identification in the last decade, focusing on individuals based on several characteristic...

Comparison of transvaginal mesh surgery and robot-assisted sacrocolpopexy for pelvic organ prolapse.

BACKGROUND: Pelvic organ prolapse (POP) is greatly affecting the quality of life (QOL) of women. There are some surgical techniques for POP repair, fo...

Using natural language processing to identify acute care patients who lack advance directives, decisional capacity, and surrogate decision makers.

The prevalence of patients who are Incapacitated with No Evident Advance Directives or Surrogates (INEADS) remains unknown because such data are not r...

Robot-Assisted General Surgery Procedures at the Veterans Health Administration: A Comparison of Surgical Techniques.

INTRODUCTION: The use of the robot in general surgery has exploded in the last decade. The Veterans Health Administration presents a unique opportunit...

Exploring the Chinese Public's Perception of Omicron Variants on Social Media: LDA-Based Topic Modeling and Sentiment Analysis.

The COVID-19 pandemic caused by SARS-CoV-2 is still raging. Similar to other RNA viruses, SARS-COV-2 is constantly mutating, which leads to the produc...

Deep learning from phylogenies to uncover the epidemiological dynamics of outbreaks.

Widely applicable, accurate and fast inference methods in phylodynamics are needed to fully profit from the richness of genetic data in uncovering the...

Integrating Deep Learning-Based IoT and Fog Computing with Software-Defined Networking for Detecting Weapons in Video Surveillance Systems.

Due to the widespread proliferation of multimedia traffic resulting from Internet of Things (IoT) applications and the increased use of remote multime...

An Explainable Transformer-Based Deep Learning Model for the Prediction of Incident Heart Failure.

Predicting the incidence of complex chronic conditions such as heart failure is challenging. Deep learning models applied to rich electronic health re...

Event-level prediction of urban crime reveals a signature of enforcement bias in US cities.

Policing efforts to thwart crime typically rely on criminal infraction reports, which implicitly manifest a complex relationship between crime, polici...

AI-Enabled Mosquito Surveillance and Population Mapping Using Dragonfly Robot.

Mosquito-borne diseases can pose serious risks to human health. Therefore, mosquito surveillance and control programs are essential for the wellbeing ...

Machine Learning-Based Regression Framework to Predict Health Insurance Premiums.

Artificial intelligence (AI) and machine learning (ML) in healthcare are approaches to make people's lives easier by anticipating and diagnosing disea...