Artificial Intelligence for Community Health Professional

Abstract

Digital health uses technologies to improve health. The article content was synthesized from PubMed, Google Scholar, and other digital resources. Artificial intelligence (AI) is a kind of a technology which has capability to assist in health and other industries. It emphasizes the simulation of human intelligence processes by machines that work and react like human beings and Machine Learning is any process by which a system improves performance from experience. It is a subset of machine learning that enables computers to solve more complex problems. Machine Learning models categorised into Supervised Learning, unsupervised and reinforcement learning. Pythan Languages is a tool which is used to build a AI programme commonly. An algorithm is a set of rules given to an AI program to help it learn on its own. Decision Trees, Support Vector Machine, Naive Bayes Classifier, Genetic Algorithms, and Fuzzy Algorithms have been used to detect and increase the accuracy of the models. The advantages of Artificial intelligence applications are enormous and can revolutionize any professional sector. In the health sector, it is primarily used for screening, monitoring, and diagnostic assistance, AI applications include algorithms that analyse chest X-rays, CT & MRI Scan, ECGs and ultrasound scan, scan pathology slides and even assess fundus images for signs of retinopathy. It helps to make better decision quick and to make new interventions, but it involves huge expense and complex technology. Ensure safety, ethically acceptable, cost-effectiveness and affordability, people-centeredness, evidence-based, effective, efficient, sustainable, inclusive, equitable and contextualized to be considered.