Abstract
Data is important for health applications. Clinicians and academics use structured and unstructured data to arrive at both diagnosis and prognosis. Artificial Intelligence (AI) plays a significant role in identifying various clinical diagnostic elements using data. These clinical diagnostic elements are not readily visible to humans. In this tutorial, we bring together academics, clinicians, health administrators from both public and private health and research scholars to discuss their experiences in developing and implementing AI-based cutting-edge healthcare and medical applications.
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Acknowledgement
We gratefully acknowledge the contributions from Dr Rashmi Gururajan (Royal Brisbane and Women’s Hospital, Brisbane), Dr Kym Boon (Royal Brisbane and Women’s Hospital, Brisbane), Professor Rajendra Udyavara Acharya (Ngee Ann, Singapore University of Social Science, Singapore), Dr Vaishnavi Moorthy (School of Computing, SRMIST-Kattankulathur Campus, Tamil Nadu-India ), Dr. Dharini Krishnan (D. V. Living Sciences Enterprise Pvt. Ltd, India) and Dr. Aparna Kasinath (Syngene International Ltd, India). Without their kind support, this tutorial would not be possible.
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Gururajan, R. et al. (2021). Emerging Applications in Healthcare and Their Implications to Academia and Practice. In: Zhang, W., Zou, L., Maamar, Z., Chen, L. (eds) Web Information Systems Engineering – WISE 2021. WISE 2021. Lecture Notes in Computer Science(), vol 13081. Springer, Cham. https://doi.org/10.1007/978-3-030-91560-5_37
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