TITLE: Revolutionizing Healthcare with Smart Computing Overview The global healthcare systems are facing unprecedented challenges driven by the rising burden of chronic and infectious diseases, an expanding and aging population, shortages of healthcare professionals, escalating costs, and unequal access to quality medical services, particularly in developing countries. Traditional healthcare systems are no longer sufficient to meet the growing and changing healthcare needs of society. The convergence of smart computing technologies including Artificial Intelligence (AI), Machine Learning (ML), the Internet of Medical Things (IoMT), Cloud and Edge computing, Big Data Analytics and Robotics is transforming the way healthcare is delivered. Among these, AI and ML have emerged as powerful enablers, capable of analyzing complex medical data such as electronic health records, medical images, genomic information, and data from wearable devices to support early disease detection, accurate diagnosis, personalized treatment, predictive analytics, continuous patient monitoring along with accurate and accelerated drug discovery. This lecture explores how smart computing is transforming healthcare through the integration of AI and other intelligent technologies to enable predictive, preventive, personalized, and participatory healthcare. It also highlights the need for responsible AI by addressing key challenges such as data privacy, explainability, fairness, and human oversight, while demonstrating how AI can support clinicians, improve patient outcomes, and enhance the efficiency, accessibility, and sustainability of healthcare systems. Presentation duration is one hour so looking about 50 slides. Include state of the art material in slides such as data, figures and statistical detail from sci journals of IEEE/NAture/BMC/Springer/Elsevier and world leading conferences..
TITLE: Revolutionizing Healthcare with Smart Computing
Overview
The global healthcare systems are facing unprecedented challenges driven by the rising burden of chronic and infectious diseases, an expanding and aging population, shortages of healthcare professionals, escalating costs, and unequal access to quality medical services, particularly in developing countries. Traditional healthcare systems are no longer sufficient to meet the growing and changing healthcare needs of society.
The convergence of smart computing technologies including Artificial Intelligence (AI), Machine Learning (ML), the Internet of Medical Things (IoMT), Cloud and Edge computing, Big Data Analytics and Robotics is transforming the way healthcare is delivered. Among these, AI and ML have emerged as powerful enablers, capable of analyzing complex medical data such as electronic health records, medical images, genomic information, and data from wearable devices to support early disease detection, accurate diagnosis, personalized treatment, predictive analytics, continuous patient monitoring along with accurate and accelerated drug discovery.
This lecture explores how smart computing is transforming healthcare through the integration of AI and other intelligent technologies to enable predictive, preventive, personalized, and participatory healthcare. It also highlights the need for responsible AI by addressing key challenges such as data privacy, explainability, fairness, and human oversight, while demonstrating how AI can support clinicians, improve patient outcomes, and enhance the efficiency, accessibility, and sustainability of healthcare systems.
Presentation duration is one hour so looking about 50 slides. Include state of the art material in slides such as data, figures and statistical detail from sci journals of IEEE/NAture/BMC/Springer/Elsevier and world leading conferences..
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This presentation explores the urgent need for smart computing in healthcare, addressing challenges like ageing populations and chronic diseases. It delves into AI-enabled healthcare, showcasing the integration of EHRs, imaging, and wearable data, while comparing various technologies. The discussion extends to responsible care, focusing on privacy, bias, and the translation of AI predictions into personalised care. The session concludes with actionable insights for adoption and future...