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  • 1. Demystifying Supervised Learning in Healthcare 4.0: A New Reality of Transforming Diagnostic Medicine

    Description:
    The global healthcare sector continues to grow rapidly and is reflected as one of the fastestgrowing sectors in the fourth industrial revolution (4.0). The majority of the healthcare industry still uses labor-intensive, time-consuming, and error-prone traditional, manual, and manpower-based methods. This review addresses the current paradigm, the potential for new scientific discoveries, the technological state of preparation, the potential for supervised machine learning (SML) prospects in various healthcare sectors, and ethical issues. The effectiveness and potential for innovation of disease diagnosis, personalized medicine, clinical trials, non-invasive image analysis, drug discovery, patient care services, remote patient monitoring, hospital data, and nanotechnology in various learning-based automation in healthcare along with the requirement for explainable artificial intelligence (AI) in healthcare are evaluated. In order to understand the potential architecture of non-invasive treatment, a thorough study of medical imaging analysis from a technical point of view is presented. This study also represents new thinking and developments that will push the boundaries and increase the opportunity for healthcare through AI and SML in the near future. Nowadays, SML-based applications require a lot of data quality awareness as healthcare is data-heavy, and knowledge management is paramount. Nowadays, SML in biomedical and healthcare developments needs skills, quality data consciousness for data-intensive study, and a knowledge-centric health management system. As a result, the merits, demerits, and precautions need to take ethics and the other effects of AI and SML into consideration. The overall insight in this paper will help researchers in academia and industry to understand and address the future research that needs to be discussed on SML in the healthcare and biomedical sectors.
    Keyword:
    Healthcare, Precision Medicine, Artificial Intelligence, Computer Vision, Deep Learning, Medical Imaging, XAI, and Supervised Learning
    Subject:
    Artificial Intelligence and Data Science
    Creator:
    Roy, Sudipta , Lim, Se-Jung , and Meena, Tanushree
    Contributor:
    Jio Institute, CVMI-Computer Vision in Medical Imaging Project
    Owner:
    n.sakthivel@jioinstitute.edu.in
    Publisher:
    MDPI
    Location:
    Switzerland and India
    Language:
    English
    Date Uploaded:
    10-02-2023
    Date Modified:
    16-02-2023
    Date Created:
    01-10-2022
    Rights Statement Tesim:
    In Copyright
    License Tesim:
    All rights reserved
    Resource Type:
    Article
    Identifier:
    10.3390/diagnostics12102549

  • 2. A Study of Obstacles in Plagiarism Software Subscribing by Colleges in Tamil Nadu

    Description:
    This article attempts to comprehend the current issues and hurdles that Indian colleges affiliated with Tamil Nadu State Universities encounter when trying to subscribe to a software that detects plagiarism. The study’s goals are to determine whether colleges employ anti-plagiarism software, whether they ensure that their student given assignments are free of copyright infringement, whether tutors teach about academic misconduct, and what people seem to think of anti-plagiarism software. We surveyed for this study and distributed the questionnaires among college administrators, principals, and librarians. The study respondents are 15.9 per cent principals, 64.2 per cent library professionals, and 19.9 per cent college administrators. The survey study report shows that 70.9 per cent of the majority of the colleges did not subscribe. 41.7 per cent gave the reason it is too expensive, and 30.5 per cent of respondents thought that for their college, it is unnecessary to subscribe. However, nobody has confirmed whether or not all colleges possess access to plagiarism detection software. Thus, according to this investigation, further Indian states must be involved in this research to understand the specific context fully. This report advises the UGC to enforce the requirement that colleges have plagiarism detection software; they either provide colleges additional money to subscribe to such software, or the university must grant free access to the affiliated colleges.
    Keyword:
    Anti-plagiarism software, Academic misconduct, Obstacles, Plagiarism software subscription, and Academic integrity
    Subject:
    Library and Information Science
    Creator:
    N., Sakthivel and A., Subaveerapandiyan
    Contributor:
    Jio Institute Digital Library
    Owner:
    n.sakthivel@jioinstitute.edu.in
    Publisher:
    DESIDOC Journal of Library and Information Technology
    Location:
    India
    Language:
    English
    Date Uploaded:
    10-02-2023
    Date Modified:
    21-03-2023
    Date Created:
    01-10-2022
    Rights Statement Tesim:
    In Copyright
    License Tesim:
    All rights reserved
    Resource Type:
    Article
    Identifier:
    10.14429/djlit.42.5.18273