Scaling of Machine Learning Techniques in Medical Imagining and Biomedical Applications Concerning Healthcare

Year : 2024 | Volume :15 | Issue : 01 | Page : 41-44
By

    Bhupinder Singh

  1. Professor, Sharda School of Law, Sharda University, Uttar Pradesh, India

Abstract

Machine learning refers to a field within computer science enabling computers to learn without explicit programming. Stemming from artificial intelligence’s study of pattern recognition and computational learning theory, machine learning develops algorithms capable of learning from vast datasets and making predictions. Its applications span diverse computing tasks like email filtering, network intrusion detection, optical character recognition, and computer vision, where conventional algorithm design proves challenging. Notably, in computer vision, a subset of computer science, machine learning plays a pivotal role. It addresses various challenges such as image recognition, object detection, and medical image processing, leveraging advancements in computing and imaging technologies. The growing complexity of biomedical data underscores the need for precise machine learning algorithms in biomedical engineering research. The fast progress of technology has a significant influence on medical science, especially in the field of imaging diagnostics. For example, computed tomography makes it possible to view interior human organs and tissues non-invasively, obviating the need for surgery. This encourages research into new, reliable, and more efficient diagnostic and treatment methods. Medical imaging, which includes biomedical signal capture, is becoming more and more important not only for therapy, monitoring the effectiveness of treatments, and rehabilitation procedures, but also for diagnosis. The growing amounts of data produced by medical diagnostic equipment make it more difficult for clinicians to manually explore and analyze the data. This paper explores the applications of machine learning in medical imagining and biomedical applications in healthcare.

Keywords: Biomedical imagining, pattern recognition, machine learning, health, medical

[This article belongs to Journal of Computer Technology & Applications(jocta)]

How to cite this article: Bhupinder Singh.Scaling of Machine Learning Techniques in Medical Imagining and Biomedical Applications Concerning Healthcare.Journal of Computer Technology & Applications.2024; 15(01):41-44.
How to cite this URL: Bhupinder Singh , Scaling of Machine Learning Techniques in Medical Imagining and Biomedical Applications Concerning Healthcare jocta 2024 {cited 2024 Apr 05};15:41-44. Available from: https://journals.stmjournals.com/jocta/article=2024/view=140225


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Regular Issue Subscription Review Article
Volume 15
Issue 01
Received March 16, 2024
Accepted March 29, 2024
Published April 5, 2024
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