Designing Machine Learning approaches for early-stage prediction of complications and risk stratification of COVID-19 patients

in Special Issue   Posted on April 9, 2021 

Information for the Special Issue

Submission Deadline: Thu 30 Sep 2021
Journal Impact Factor : 1.916
Journal Name : Medical and Biological Engineering and Computing
Journal Publisher:
Website for the Special Issue: https://www.springer.com/journal/11517/updates/19039740
Journal & Submission Website: https://www.springer.com/journal/11517

Special Issue Call for Papers:

Medical & Biological Engineering & Computing is now accepting submissions to an upcoming special issue, entitled:

Designing Machine Learning approaches for early-stage prediction of complications and risk stratification of COVID-19 patientsCall for PapersGuest Editors

The worldwide emergency sparked by the COVID-19 pandemic has highlighted the need for a predictive care model capable of providing an accurate estimate of resources and preventive medicine. New machine learning algorithms developed thanks to widely-available EHR data and deep learning techniques have the potential to fulfill this need. This special issue aims to cover all research related to Machine Learning (ML) and Deep Learning (DL) methodologies in providing risk profiles of individual patients in intensive and non-intensive care units from which a different intensity of care can be deduced. We hope that this collection promotes synergy between the machine learning and biomedical communities as they develop new methods to overcome obstacles posed by COVID. Review the Call for Papers document above for additional details and acceptable topics.

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Submission Deadline: September 30, 2021