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

2 publications

  • Published Subscription Original Research

    Early Detection of Alzheimer’s Disease Using Machine Learning Techniques

    By K.Surendra Reddy, Kuruva Ramanjaneyulu, Daggulu Lakshmi Charitha, M.Rani, K.Mohammad Muddasir, Ch.Thirupathamma, N. Naveen

    Abstract: Alzheimer's Disease (AD) is a progressive neurodegenerative condition impacting a large global population. Detecting AD early is critical for timely intervention and effective management. Conventional diagnostic approaches involve cognitive assessments and neuroimaging, which are often lengthy, costly, and prone to human error. In this paper, we propose a novel approach for early detection of AD using machine learning techniques applied to multimodal data, including neuroimaging, cognitive assessments, and biomarkers. Our …

    Published in Research and Reviews: A Journal of Neuroscience · Vol. 14, Issue 2, 2024 · pp. 32–43 Read article

  • Published Subscription Original Research

    Enhancing Cancer Diagnosis: AI/ML Algorithms and Nanotechnology-Based Biosensors for Colorectal Cancer Screening

    By K.Surendra Reddy, Kuruva Ramanjaneyulu, Daggulu Lakshmi Charitha, M.Rani, K.Mohammad Muddasir, Ch.Thirupathamma,, N.Naveen

    Abstract: Colorectal cancer (CRC) is one of the most common and deadly cancers worldwide, and enhancing patient outcomes requires early identification. This study explores the potential of nanotechnology- enhanced biosensors and artificial intelligence/machine learning (AI/ML) algorithms to revolutionize colorectal cancer screening and diagnosis. Nanotechnology offers unique opportunities for the development of highly sensitive and specific biosensors capable of detecting cancer biomarkers at an early stage. By incorporating nanomaterials with exceptional optical, …

    Published in Nano Trends – A Journal of Nano Technology & Its Applications · Vol. 26, Issue 1, 2024 · pp. 16–28 Read article

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