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  <titleInfo>
    <title>Evolution of machine learning and internet of things applications in biomedical engineering</title>
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  <name type="personal">
    <namePart>Rana, Arun Kumar</namePart>
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  <name type="personal">
    <namePart>Sharma, Vishnu</namePart>
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  <name type="personal">
    <namePart>Rana, Sanjeev Kumar</namePart>
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      <roleTerm type="text">editor.</roleTerm>
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  <name type="personal">
    <namePart>Chaudhary, Vijay Shanker</namePart>
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    <dateIssued encoding="marc">2025</dateIssued>
    <edition>First edition.</edition>
    <issuance>monographic</issuance>
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    <languageTerm authority="iso639-2b" type="code">eng</languageTerm>
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  <abstract>"This book provides a platform for presenting machine learning-enabled healthcare techniques and offers a mathematical and conceptual background of the latest technology. It describes machine learning techniques along with the emerging platform of the Internet of Medical Things used by practitioners and researchers around the world. Evolution of Machine Learning and Internet of Things Applications in Biomedical Engineering discusses IoT and ML devices that are deployed for enabling patient health tracking, various emergency issues, and the smart administration of patients. It looks at the problems of cardiac analysis in e-healthcare, explores the employment of smart devices aimed for different patient issues, and examines the usage of Arduino kits where the data can be transferred to cloud for internet-based uses. The book includes deep feed forward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology. The authors also examine the role of IoT and ML in electroencephalography (EEG) and magnetic resonance imaging (MRI), which play significant roles in biomedical applications. This book also incorporates the use of IoT and ML applications for smart wheelchairs, telemedicine, GPS positioning of heart patients, and smart administration with drug tracking. Finally, the book also presents the application of these technologies in the development of advanced healthcare frameworks. This book will be beneficial for new researchers and practitioners working in the biomedical and healthcare fields. It will also be suitable for a wide range of readers who may not be scientists but who are also interested in the practices of medical image retrieval, and brain image segmentation"--</abstract>
  <tableOfContents>Applications of Artificial Intelligence and Internet of Things in Healthcare Industries / A. Ameer Rashed Khan, Muhammad Ilyas R N, and M. Nagoor Meeral -- ML for Internet of Medical Things Applications : Framework, Developments, and Challenges / Divneet Kaur, Bharatdeep Singh, and Sita Rani -- IoT Healthcare's Advanced Decision Support through Computational Intelligence / Pawan Whig, Jhansi Bharathi Madavarapu, Nikhitha Yathiraju, and Ramya Thatikonda -- Insights into Thyroid Disease : Harnessing Machine Learning for Analysis and Classification of Multi-Label Medical Data / Shalu Surendran and Umme Salma M. -- Longitudinal Study on Non-Communicable Diseases Using Machine Learning / Joshua K Deepak and Umme Salma M -- Uncovering Machine Learning Trends in Biomedical : Pulmonary Disease Diagnosis / Anish Singh, Atul Kabra, and Anupam Bonkra -- Smart Surgery : Navigating Precision through Machine Learning and IoT / Anita Mohanty, Ambarish G. Mohapatra, and Subrat Kumar Mohanty -- Classification and Detection of Brain Tumors in MRI Images Using Machine Learning Techniques / Ganesh Khekare, Gaurav Kumar Ameta, Rahul Sharma, Anil Turukmane, Pooja Sharma, Urvashi Khekare, and Rahul Agrawal -- Advanced Deep Learning for Early Alzheimer's Detection : A Comparative Analysis / Deepika Roselind Johnson, Logeswari G, and Sudhakaran G -- Artificial Intelligence and Machine Learning in Biomedical Signal Processing / Aditya Kumar, Niharika Koch, Sk Imran, and Jainath Yadav -- Machine Learning and Internet of Things Biomedical Technologies / Ruchin Kacker, Sanjay Kumar Singh, and Amit Arora -- Revolutionizing Chronic Kidney Disease Prediction : An Enhanced Semi-Supervised Learning Model / G.Logeswari, J.Deepika Roselind, and G. Sudhakaran -- Analysing the Seamless Integration of Machine Learning and Internet of Things in the Daily Dynamics of Contemporary Living / Kanchan Naithani, Y. P. Raiwani, and Shrikant Tiwari -- Convergence of AR, VR, IoT with Artificial Intelligence to train Surgeons for Medical Surgeries / Rishabh Jha, Amrita Singh, and Arun Kumar Rana -- An overview of IoT &amp; Machine Learning Approach in Health Care / Niva Tripathy, Subhranshu Sekhar Tripathy, and Subhendu Kumar Pani -- Healthcare Unbound : Navigating Emerging Trends and Future Applications in IoT-Based Innovations for Daily Well-being / Mrunalini H Kulkarni and Poonam R Inamdar -- Image Guided Surgery Through ML and IOT / Pallavi Pandey and Priyanka Gauniya.</tableOfContents>
  <note type="statement of responsibility">edited by Arun Kumar Rana, Vishnu Sharma, Sanjeev Kumar Rana, and Vijay Shanker Chaudhary.</note>
  <subject authority="lcsh">
    <topic>Biomedical engineering</topic>
  </subject>
  <classification authority="lcc">R855.3</classification>
  <relatedItem type="series">
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      <title>Emerging trends in biomedical technologies and health informatics series</title>
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  <identifier type="isbn">9781003476207</identifier>
  <identifier type="isbn">1003476201</identifier>
  <identifier type="isbn">9781040149362</identifier>
  <identifier type="isbn">1040149367</identifier>
  <identifier type="isbn">9781040149348</identifier>
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