Literature DB >> 35838976

Machine Learning Approaches to Analyze MALDI-TOF Mass Spectrometry Protein Profiles.

Lucas C Lazari1, Livia Rosa-Fernandes1, Giuseppe Palmisano2.   

Abstract

Machine learning is being employed for the development of diagnostic methods for several diseases, but prognostic techniques are still poorly explored. The development of such approaches is essential to assist healthcare workers to ensure the most appropriate treatment for patients. In this chapter, we demonstrate a detailed protocol for the application of machine learning to MALDI-TOF MS spectra of COVID-19-infected plasma samples for risk classification and biomarker identification.
© 2022. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.

Entities:  

Keywords:  Biomarkers; COVID-19; Classification; MALDI-TOF; Machine learning; Prognostic

Mesh：

Substances：

Year:  2022        PMID： 35838976     DOI： 10.1007/978-1-0716-2395-4_29

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN： 1064-3745


  8 in total

1.  Prognostic accuracy of MALDI-TOF mass spectrometric analysis of plasma in COVID-19.

Authors:  Lucas Cardoso Lazari; Fabio De Rose Ghilardi; Livia Rosa-Fernandes; Diego M Assis; José Carlos Nicolau; Veronica Feijoli Santiago; Talia Falcão Dalçóquio; Claudia B Angeli; Adriadne Justi Bertolin; Claudio Rf Marinho; Carsten Wrenger; Edison Luiz Durigon; Rinaldo Focaccia Siciliano; Giuseppe Palmisano
Journal:  Life Sci Alliance       Date:  2021-06-24

2.  Development of machine learning models for diagnosis of glaucoma.

Authors:  Seong Jae Kim; Kyong Jin Cho; Sejong Oh
Journal:  PLoS One       Date:  2017-05-23       Impact factor: 3.240

3.  Upregulated IL-6 Indicates a Poor COVID-19 Prognosis: A Call for Tocilizumab and Convalescent Plasma Treatment.

Authors:  Jian Wu; Jiawei Shen; Ying Han; Qinghua Qiao; Wei Dai; Bangshun He; Rongrong Pang; Jun Zhao; Tao Luo; Yanju Guo; Yang Yang; Qiuyue Wu; Weijun Jiang; Jing Zhang; Mingchao Zhang; Na Li; Weiwei Li; Xinyi Xia
Journal:  Front Immunol       Date:  2021-03-04       Impact factor: 7.561

4.  Machine learning-based prediction of COVID-19 diagnosis based on symptoms.

Authors:  Yazeed Zoabi; Shira Deri-Rozov; Noam Shomron
Journal:  NPJ Digit Med       Date:  2021-01-04

5.  COVID-Classifier: an automated machine learning model to assist in the diagnosis of COVID-19 infection in chest X-ray images.

Authors:  Abolfazl Zargari Khuzani; Morteza Heidari; S Ali Shariati
Journal:  Sci Rep       Date:  2021-05-10       Impact factor: 4.379

6.  Effect of asthma and asthma medication on the prognosis of patients with COVID-19.

Authors:  Yong Jun Choi; Ju-Young Park; Hye Sun Lee; Jin Suh; Jeung Yoon Song; Min Kwang Byun; Jae Hwa Cho; Hyung Jung Kim; Jae-Hyun Lee; Jung-Won Park; Hye Jung Park
Journal:  Eur Respir J       Date:  2021-03-04       Impact factor: 16.671

7.  Prediction models for diagnosis and prognosis of covid-19: systematic review and critical appraisal

Authors:  Laure Wynants; Ben Van Calster; Gary S Collins; Richard D Riley; Georg Heinze; Ewoud Schuit; Marc M J Bonten; Darren L Dahly; Johanna A A Damen; Thomas P A Debray; Valentijn M T de Jong; Maarten De Vos; Paul Dhiman; Maria C Haller; Michael O Harhay; Liesbet Henckaerts; Pauline Heus; Michael Kammer; Nina Kreuzberger; Anna Lohmann; Kim Luijken; Jie Ma; Glen P Martin; David J McLernon; Constanza L Andaur Navarro; Johannes B Reitsma; Jamie C Sergeant; Chunhu Shi; Nicole Skoetz; Luc J M Smits; Kym I E Snell; Matthew Sperrin; René Spijker; Ewout W Steyerberg; Toshihiko Takada; Ioanna Tzoulaki; Sander M J van Kuijk; Bas van Bussel; Iwan C C van der Horst; Florien S van Royen; Jan Y Verbakel; Christine Wallisch; Jack Wilkinson; Robert Wolff; Lotty Hooft; Karel G M Moons; Maarten van Smeden
Journal:  BMJ       Date:  2020-04-07
  8 in total

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