AutoML Systems For Medical Imaging

• URL: http://arxiv.org/abs/2306.04750v2
• Date: Sat, 17 Jun 2023 17:24:05 GMT
• Title: AutoML Systems For Medical Imaging
• Authors: Tasmia Tahmida Jidney, Angona Biswas, MD Abdullah Al Nasim, Ismail Hossain, Md Jahangir Alam, Sajedul Talukder, Mofazzal Hossain, Dr. Md Azim Ullah
• Abstract summary: The integration of machine learning in medical image analysis can greatly enhance the quality of healthcare provided by physicians. An automated machine learning approach simplifies the creation of custom image recognition models. Medical imaging techniques are used to non-invasively create images of internal organs and body parts for diagnostic and procedural purposes.
• Score: 5.581919089808456
• License: http://creativecommons.org/publicdomain/zero/1.0/
• Abstract: The integration of machine learning in medical image analysis can greatly enhance the quality of healthcare provided by physicians. The combination of human expertise and computerized systems can result in improved diagnostic accuracy. An automated machine learning approach simplifies the creation of custom image recognition models by utilizing neural architecture search and transfer learning techniques. Medical imaging techniques are used to non-invasively create images of internal organs and body parts for diagnostic and procedural purposes. This article aims to highlight the potential applications, strategies, and techniques of AutoML in medical imaging through theoretical and empirical evidence.

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