AIMC Topic: Humans

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COVID-19 Patient Health Prediction Using Boosted Random Forest Algorithm.

Frontiers in public health
Integration of artificial intelligence (AI) techniques in wireless infrastructure, real-time collection, and processing of end-user devices is now in high demand. It is now superlative to use AI to detect and predict pandemics of a colossal nature. T...

COVID-19 Coronavirus Vaccine Design Using Reverse Vaccinology and Machine Learning.

Frontiers in immunology
To ultimately combat the emerging COVID-19 pandemic, it is desired to develop an effective and safe vaccine against this highly contagious disease caused by the SARS-CoV-2 coronavirus. Our literature and clinical trial survey showed that the whole vi...

Application of Artificial Intelligence in COVID-19 drug repurposing.

Diabetes & metabolic syndrome
BACKGROUND AND AIM: COVID-19 outbreak has created havoc and a quick cure for the disease will be a therapeutic medicine that has usage history in patients to resolve the current pandemic. With technological advancements in Artificial Intelligence (AI...

The art of atom descriptor design.

Drug discovery today. Technologies
This review provides an overview of descriptions of atoms applied to the understanding of phenomena like chemical reactivity and selectivity, pK values, Site of Metabolism prediction, or hydrogen bond strengths, but also the substitution of quantum m...

Differentiation Between Anteroposterior and Posteroanterior Chest X-Ray View Position With Convolutional Neural Networks.

RoFo : Fortschritte auf dem Gebiete der Rontgenstrahlen und der Nuklearmedizin
PURPOSE:  Detection and validation of the chest X-ray view position with use of convolutional neural networks to improve meta-information for data cleaning within a hospital data infrastructure.

From CT to artificial intelligence for complex assessment of plaque-associated risk.

The international journal of cardiovascular imaging
The recent technological developments in the field of cardiac imaging have established coronary computed tomography angiography (CCTA) as a first-line diagnostic tool in patients with suspected coronary artery disease (CAD). CCTA offers robust inform...

A deep learning approach to characterize 2019 coronavirus disease (COVID-19) pneumonia in chest CT images.

European radiology
OBJECTIVES: To utilize a deep learning model for automatic detection of abnormalities in chest CT images from COVID-19 patients and compare its quantitative determination performance with radiological residents.

Self-supervised learning of physics-guided reconstruction neural networks without fully sampled reference data.

Magnetic resonance in medicine
PURPOSE: To develop a strategy for training a physics-guided MRI reconstruction neural network without a database of fully sampled data sets.

Digitalization, clinical microbiology and infectious diseases.

Clinical microbiology and infection : the official publication of the European Society of Clinical Microbiology and Infectious Diseases

The novel approaches to classify cyclist accident injury-severity: Hybrid fuzzy decision mechanisms.

Accident; analysis and prevention
In this study, two novel fuzzy decision approaches, where the fuzzy logic (FL) model was revised with the C4.5 decision tree (DT) algorithm, were applied to the classification of cyclist injury-severity in bicycle-vehicle accidents. The study aims to...