Applications of Artificial Intelligence and Machine Learning in Healthcare

  • Author : Hassan Alamoudi
  • Publsiher : Anonim
  • Release : 13 April 2021
  • ISBN : OCLC:1139617986
  • Page : 123 pages
  • Rating : 4/5 from 21 voters

Download or read online book entitled Applications of Artificial Intelligence and Machine Learning in Healthcare written by Hassan Alamoudi and published by Anonim. This book was released on 13 April 2021 with total page 123 pages. Available in PDF, EPUB and Kindle. Get best books that you want by click Get Book Button and Read as many books as you like. Book Excerpt : Artificial Intelligence (AI) is becoming a ubiquitous term that is used in many fields of research or the popular culture. Among these fields that was affected by this hype is the healthcare sector. Along with its subdomain, Machine Learning (ML), they established an environment of interest in the promises of machines versus humans capabilities. Though artificial intelligence applications in healthcare such as interpreting ECGs could date back to the mid of the twentieth century, the promises of AI still at its beginning when it comes to new breakthroughs. This is due to the transformation into a digital world and new advancements in the processing capabilities. Computer vision has contributed the most to the healthcare sector where it can leverage doctors and practitioners with automated classification and annotations as a preparing step. This kind of mechanism is the best suited for applications of AI in healthcare. However, the amount of data in other forms such as textual or lab results is exceeding the force power. While a solution could be to use machines to learn and propose solutions, the results could be catastrophic and human lives are on stake. So, explainable AI could be beneficial where it analyzes and makes predictions that can be trusted by the users. The study here is conducted on cardiovascular patients dataset to predict the presence or absence of the disease. Classifications techniques used include Nave Bayes, Logistic Regression, Decision Trees, Support Vector Machines, and Artificial Neural Networks. The Logistic regression model achieved the best Area under the curve. Moreover, an extension of the previous studies discussed is conducted to explain the model and to show how models of AI can be trusted and not used as black-boxes.

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