AIMC Topic: COVID-19

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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 ...

Is the generalizability of a developed artificial intelligence algorithm for COVID-19 on chest CT sufficient for clinical use? Results from the International Consortium for COVID-19 Imaging AI (ICOVAI).

European radiology
OBJECTIVES: Only few published artificial intelligence (AI) studies for COVID-19 imaging have been externally validated. Assessing the generalizability of developed models is essential, especially when considering clinical implementation. We report t...

Benchmarking of Machine Learning classifiers on plasma proteomic for COVID-19 severity prediction through interpretable artificial intelligence.

Artificial intelligence in medicine
The SARS-CoV-2 pandemic highlighted the need for software tools that could facilitate patient triage regarding potential disease severity or even death. In this article, an ensemble of Machine Learning (ML) algorithms is evaluated in terms of predict...

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...

Optimizing variant-specific therapeutic SARS-CoV-2 decoys using deep-learning-guided molecular dynamics simulations.

Scientific reports
Treatment of COVID-19 with a soluble version of ACE2 that binds to SARS-CoV-2 virions before they enter host cells is a promising approach, however it needs to be optimized and adapted to emerging viral variants. The computational workflow presented ...

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...

MT-nCov-Net: A Multitask Deep-Learning Framework for Efficient Diagnosis of COVID-19 Using Tomography Scans.

IEEE transactions on cybernetics
The localization and segmentation of the novel coronavirus disease of 2019 (COVID-19) lesions from computerized tomography (CT) scans are of great significance for developing an efficient computer-aided diagnosis system. Deep learning (DL) has emerge...

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...

Decision Method of Optimal Needle Insertion Angle for Dorsal Hand Intravenous Robot.

Sensors (Basel, Switzerland)
In the context of COVID-19, the research on various aspects of the venipuncture robot field has become increasingly hot, but there has been little research on robotic needle insertion angles, primarily performed at a rough angle. This will increase t...

Coronavirus covid-19 detection by means of explainable deep learning.

Scientific reports
The coronavirus is caused by the infection of the SARS-CoV-2 virus: it represents a complex and new condition, considering that until the end of December 2019 this virus was totally unknown to the international scientific community. The clinical mana...