STM Journals Peer-reviewed research from Consortium e-Learning Network

3 publications

  • Published Subscription Review Article

    Ethical Challenges in Natural Language Processing: A Comparative Study of Solutions Across Multiple Domains

    By Khushi Singh, Sheetal Singh, Aritro Chakraborty, Himanshu Singh, Sujeet Kumar

    Abstract: This comparative analysis investigates the ethical challenges associated with natural language processing (NLP) by reviewing and synthesizing insights from ten influential and widely cited publications in the field. As NLP technologies are increasingly integrated into domains such as healthcare, finance, education, and governance, ethical concerns related to algorithmic bias, data privacy, fairness, accountability, and system transparency have become more prominent. This paper systematically examines how different researchers conceptualize and address …

    Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 13, Issue 1, 2026 · pp. 01–07 Read article

  • Published Subscription Review Article

    Natural Language Processing in Everyday Applications: From Classrooms to Clinics

    By Aritro Chakraborty, Sheetal Singh, Khushi Singh, Sujeet Kumar, Mukesh Kumar

    Abstract: Natural Language Processing (NLP) is transforming everyday sectors like healthcare and education by creating new opportunities for efficiency, accessibility, and early intervention. This paper investigates the function of natural language processing (NLP) in computer education. Tools like automated grading systems, intelligent tutoring assistants, and multilingual translation platforms are revolutionizing traditional teaching methods. Despite its benefits, adoption is still being slowed down by problems like data privacy, integration with education, and …

    Published in Research and Reviews: A Journal of Health Professions · Vol. 15, Issue 3, 2025 Read article

  • Published Subscription Review Article

    Data to Diagnosis: A Systematic Review of AI/ML in Healthcare

    By Sheetal Singh, Khushi Singh, Sujeet Kumar, Aritro Chakraborty, Harshal Singh

    Abstract: Artificial Intelligence (AI) and Machine Learning (ML) are fast revolutionizing the diagnosis of healthcare by augmenting accuracy, speed, and efficiency. AI/ML technologies facilitate earlier and more accurate disease identification with advanced algorithms for image processing, predictive modelling, and pattern recognition, frequently outperforming conventional diagnostic techniques. This review delves into the key contribution of AI/ML in contemporary healthcare, such as its use in clinical data analysis, imaging reports, and patient histories …

    Published in International Journal of Biomedical Innovations and Engineering · Vol. 3, Issue 2, 2025 Read article

Support