Journal – Indian Journal of Surgery
Publication date – Oct – 2020
Authors – Vikesh Agrawal, Dhananjaya Sharma & Sanjay Kumar Yadav
Keywords – Artificial Intelligence, Deep Learning, machine learning, Resource Optimization, surgery
Open access – Yes
Speciality – Health policy
World region South-eastern Asia
Country: India
Language – English
Submitted to the One Surgery Index on November 12, 2020 at 9:50 am
Abstract:

Dear Editor,

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.

OSI Number – 20741
PMID – 33106738

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