AIMC Topic: Pandemics

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Spatial and deep learning analyses of urban recovery from the impacts of COVID-19.

Scientific reports
This study investigates urban recovery from the COVID-19 pandemic by focusing on three main types of working, commercial, and night-life activities and associating them with land use and inherent socio-economic patterns as well as points of interests...

Prediction models for the impact of the COVID-19 pandemic on research activities of Japanese nursing researchers using deep learning.

Japan journal of nursing science : JJNS
AIM: This study aimed to construct and evaluate prediction models using deep learning to explore the impact of attributes and lifestyle factors on research activities of nursing researchers during the COVID-19 pandemic.

Early Identification of Crop Type for Smallholder Farming Systems Using Deep Learning on Time-Series Sentinel-2 Imagery.

Sensors (Basel, Switzerland)
Climate change and the COVID-19 pandemic have disrupted the food supply chain across the globe and adversely affected food security. Early estimation of staple crops can assist relevant government agencies to take timely actions for ensuring food sec...

Multi-objective optimization determines when, which and how to fuse deep networks: An application to predict COVID-19 outcomes.

Computers in biology and medicine
The COVID-19 pandemic has caused millions of cases and deaths and the AI-related scientific community, after being involved with detecting COVID-19 signs in medical images, has been now directing the efforts towards the development of methods that ca...

Socioexposomics of COVID-19 across New Jersey: a comparison of geostatistical and machine learning approaches.

Journal of exposure science & environmental epidemiology
BACKGROUND: Disparities in adverse COVID-19 health outcomes have been associated with multiple social and environmental stressors. However, research is needed to evaluate the consistency and efficiency of methods for studying these associations at lo...

A survey of machine learning-based methods for COVID-19 medical image analysis.

Medical & biological engineering & computing
The ongoing COVID-19 pandemic caused by the SARS-CoV-2 virus has already resulted in 6.6 million deaths with more than 637 million people infected after only 30 months since the first occurrences of the disease in December 2019. Hence, rapid and accu...

Re-envisioning the design of nanomedicines: harnessing automation and artificial intelligence.

Expert opinion on drug delivery
INTRODUCTION: Interest in nanomedicines has surged in recent years due to the critical role they have played in the COVID-19 pandemic. Nanoformulations can turn promising therapeutic cargo into viable products through improvements in drug safety and ...

A hybrid deep learning framework for air quality prediction with spatial autocorrelation during the COVID-19 pandemic.

Scientific reports
China implemented a strict lockdown policy to prevent the spread of COVID-19 in the worst-affected regions, including Wuhan and Shanghai. This study aims to investigate impact of these lockdowns on air quality index (AQI) using a deep learning framew...

Same day discharge for robot-assisted radical prostatectomy: a prospective cohort study documenting an Australian approach.

ANZ journal of surgery
BACKGROUND: The introduction of robotic surgical systems has significantly impacted urological surgery, arguably more so than other surgical disciplines. The focus of our study was length of hospital stay - patients have traditionally been discharged...

Study on the Applicability of Digital Twins for Home Remote Motor Rehabilitation.

Sensors (Basel, Switzerland)
The COVID-19 pandemic created the need for telerehabilitation development, while Industry 4.0 brought the key technology. As motor therapy often requires the physical support of a patient's motion, combining robot-aided workouts with remote control i...