AI Medical Compendium Topic

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Hemorrhagic Fever, Ebola

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Transforming Clinical Data into Actionable Prognosis Models: Machine-Learning Framework and Field-Deployable App to Predict Outcome of Ebola Patients.

PLoS neglected tropical diseases
BACKGROUND: Assessment of the response to the 2014-15 Ebola outbreak indicates the need for innovations in data collection, sharing, and use to improve case detection and treatment. Here we introduce a Machine Learning pipeline for Ebola Virus Diseas...

Comparison of machine learning methods for estimating case fatality ratios: An Ebola outbreak simulation study.

PloS one
BACKGROUND: Machine learning (ML) algorithms are now increasingly used in infectious disease epidemiology. Epidemiologists should understand how ML algorithms behave within the context of outbreak data where missingness of data is almost ubiquitous.

Inaccuracies in Google's Health-Based Knowledge Panels Perpetuate Widespread Misconceptions Involving Infectious Disease Transmission.

The American journal of tropical medicine and hygiene
Google health-based Knowledge Panels were designed to provide users with high-quality basic medical information on a specific condition. However, any errors contained within Knowledge Panels could result in the widespread distribution of inaccurate h...

Toward a Coronavirus Knowledge Graph.

Genes
This study builds a coronavirus knowledge graph (KG) by merging two information sources. The first source is Analytical Graph (AG), which integrates more than 20 different public datasets related to drug discovery. The second source is CORD-19, a col...

Automatic detection and classification of lung cancer CT scans based on deep learning and ebola optimization search algorithm.

PloS one
Recently, research has shown an increased spread of non-communicable diseases such as cancer. Lung cancer diagnosis and detection has become one of the biggest obstacles in recent years. Early lung cancer diagnosis and detection would reliably promot...

Automatic face detection based on bidirectional recurrent neural network optimized by improved Ebola optimization search algorithm.

Scientific reports
Face detection is a multidisciplinary research subject that employs fundamental computer algorithms, image processing, and patterning. Neural networks, on the other hand, have been widely developed to solve challenges in the domains of feature extrac...

Supervised learning approaches for predicting Ebola-Human Protein-Protein interactions.

Gene
The goal of this research work is to predict protein-protein interactions (PPIs) between the Ebola virus and the host who is at risk of infection. Since there are very limited databases available on the Ebola virus; we have prepared a comprehensive d...

Artificial neural network-driven modeling of Ebola transmission dynamics with delays and disability outcomes.

Computational biology and chemistry
This study develops an Artificial Neural Network (ANN)-based framework to model the transmission dynamics and long-term disability outcomes of Ebola Virus Disease (EVD). Building on existing deterministic SEIR models, we extend the framework by intro...

Decoding the blueprint of receptor binding by filoviruses through large-scale binding assays and machine learning.

Cell host & microbe
Evidence suggests that bats are important hosts of filoviruses, yet the specific species involved remain largely unidentified. Niemann-Pick C1 (NPC1) is an essential entry receptor, with amino acid variations influencing viral susceptibility and spec...

Assessing concordance between RNA-Seq and NanoString technologies in Ebola-infected nonhuman primates using machine learning.

BMC genomics
This study evaluates the concordance between RNA sequencing (RNA-Seq) and NanoString technologies for gene expression analysis in non-human primates (NHPs) infected with Ebola virus (EBOV). A detailed comparison of both platforms revealed a strong co...