Abstract
The growth in information technology and computer capacity has opened up opportunities to deal with much and much larger data sets than even a decade ago. There has been a technological revolution of big data and Artificial Intelligence (AI). Perhaps many readers would immediately think about robotic surgery or self-driving cars, but there is much more to AI. This Short Communication starts with an overview of the key terms, including AI, machine learning, deep learning and Big Data.This Short Communication highlights so developments of AI in health that could benefit a low-income country like Nepal and stresses the need for Nepal’s health and education systems to track such developments and apply them locally. Moreover, Nepal needs to start growing its own AI expertise to help develop national or South Asian solutions. This would require investing in local resources such as access to computer power/capacity as well as training young Nepali to work in AI.
Highlights
The growth in information technology and computer capacity has opened up opportunities to deal with much and much larger data sets than even a decade ago
There has been a technological revolution of big data and Artificial Intelligence (AI)
This Short Communication starts with an overview of the key terms, including AI, machine learning, deep learning and Big Data
Summary
The growth in information technology and computer capacity has opened up opportunities to deal with much and much larger data sets than even a decade ago. Perhaps many readers would immediately think about robotic surgery or self-driving cars, but there is much more to AI This Short Communication starts with an overview of the key terms, including AI, machine learning, deep learning and Big Data. The concept of (longitudinal) big data becomes quite appealing as data from different sources in various format (text, image, numerical, video) can be combined to make well-informed diagnosis or prognosis decisions. These electronic health databases can allow for a personalized approach to medicine by improving diagnoses and predicting individual therapy responses, within clinical research and practice this would constitute a revolution if successful.
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