Article

COMPARATIVE PERFORMANCE OF TWO AUTOMATED MACHINE LEARNING PLATFORMS FOR COVID-19 DETECTION BY MALDI-TOF-MS

2022-02-04

Abstract excerpt

<h4>ABSTRACT</h4> The 2019 novel coronavirus infectious disease (COVID-19) pandemic has resulted in an unsustainable need for diagnostic tests. Currently, molecular tests are the accepted standard for the detection of SARS-CoV-2. Mass spectrometry (MS) enhanced by machine learning (ML) has recently been postulated to serve as a rapid, high-throughput, and low-cost alternative to molecular methods. Automated ML is...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: 2be037d2-b6c5-5c7a-bc51-460c0791ced5
DOI: 10.1101/2022.02.02.22270298

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 8 closest

COMPARATIVE PERFORMANCE OF TWO AUTOMATED MACHINE LEARNING PLATFORMS FOR COVID-19 DETECTION BY MALDI-TOF-MSDOI 10.1101/2022.02.02.22270298Read

Machine Learning Data Processing for COVID‐19 DiagnosticsSemantic proximity Read

Automated machine learning optimizes and accelerates predictive modeling from COVID-19 high throughput datasetsSemantic proximity Read

Transparent exploration of machine learning for biomarker discovery from proteomics and omics dataSemantic proximity Read

A rigorous evaluation of optimal peptide targets for MS-based clinical diagnostics of Coronavirus Disease 2019 (COVID-19)Semantic proximity Read

An adaptive, continuous-learning framework for clinical decision-making from proteome-wide biofluid dataSemantic proximity Read

Using Automated-Machine Learning to Predict COVID-19 Patient Survival: Identify Influential BiomarkersSemantic proximity Read

Development of an Accurate AI/ML-Driven COVID-19 Patient Stratification Model Predicting Disease Outcomes from Disproportionate and Scarce Clinical DatasetsSemantic proximity Read

Application of omics technology to combat the COVID‐19 pandemicSemantic proximity Read