key: cord-0051879-xjor3ys9
authors: Agrawal, Vikesh; Sharma, Dhananjaya; Yadav, Sanjay Kumar
title: Letter to Editor: “Artificial Intelligence, Machine Learning, Deep Learning and Big Data Analytics for Resource Optimization in Surgery”
date: 2020-10-21
journal: Indian J Surg
DOI: 10.1007/s12262-020-02643-8
sha: 6c51d55be7c77b4c7d8d8abc9a8a077d6e7de936
doc_id: 51879
cord_uid: xjor3ys9

nan

Health care delivery in the pandemic is heavily disrupted. There are high stakes and economic implications are huge especially in more vulnerable low and middle-income group countries (LMICs). It is even more imperative now that we optimize our resources. Artificial intelligence (AI) and its exploits should now be requisitioned. Two subsets of AI are machine learning (ML) which in turn enables deep learning (DL). Big data are analyzed [1] . Such tasks are complex and will require yeoman efforts both on the parts individuals and governments. The respective state and central governments will provide regulatory sanctions. Preparations into big data analysis, machine learning leading to deep learning is likely to save resources. The current pandemic has amply shown this and should prompt us to invest in AI. Efforts and investment in deep learning should be translational in resource allocation and resource triage even during normal settings. We have written an iterative algorithm that should convince the stakeholders to invest in this modality (Fig. 1 

The Riyadh Declaration: the role of digital health in fighting pandemics

Conflict of Interest The authors declare that they have no conflict of interest.Publisher's Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.