Information and Communication Technologies and Healthcare

This lecture series is part of the Asi@Connect project Intelligent Medical Services over TEIN (http://ims-tein.com).

Health-care has evolved with the use of ICT for providing quality health services. This lecture series will provide you the details of state of the art technologies and their role in advancement of health-care domain. You will learn the basics about the technologies such as Internet of Things, Machine Learning, Deep Learning, and Big Data, and their role in health-care/ medical applications.

Length	1 Month
Lecture Time	25 to 50 minutes
Course Subscription	Free
Target Audience	Target Audience
Target Location	This lecture series is intended for beneficiaries of Asi@Conenct TEIN CC project only.
Language	English

Course Materials

You will learn the basics about the technologies such as Internet of Things, Machine Learning, Deep Learning, and Big Data, and their role in health-care/ medical applications.

Course Content

Expand All | Collapse All

Lessons Status

Influence of ICT on Medical

This lectures provides insights into Internet of Things (IoT) and its applications in the medical domain. Lecture contents deal with the overall IoT process and discussed in detail different aspects of medical informatics and its use cases.

Internet of Medical Things

This lecture describes the role of ICT in health-care domain. It outlines the overall health-care ecosystem with ICT technologies. The research trends in health-care domain utilizing ICT technologies, and the state of the art technologies are also highlighted.

Machine Learning in Health-care

This lecture presents the impact of big data on the health-care domain. Challenges and opportunities regarding big data are discussed in detail. Furthermore, different big data technologies such as Hadoop are explored in order to provide a powerful infrastructure for innovative medical applications.

Deep Learning for Medical Imaging

The lecture addresses the role of deep learning in medical imaging. It also highlights different use cases of deep learning in medical domain. The lecture contents include discussion regarding different deep learning architectures in the context of medical imaging. In this regard, a comparative analysis of conventional machine vision system and convolutional neural network system is provided in order to grasp the merits of deep learning technology.

Big Data in Health-care

This lecture explores machine learning and its types. Also, it identifies the impact of machine learning on health-care domain. The lecture contents deal with a big picture introduction of machine learning techniques. Furthermore, healthcare applications are discussed which can benefit from machine learning in terms of decision automation.

Information and Communication Technologies and Healthcare

Information and Communication Technologies and Healthcare

Course Materials

Course Content

Influence of ICT on Medical This lectures provides insights into Internet of Things (IoT) and its applications in the medical domain. Lecture contents deal with the overall IoT process and discussed in detail different aspects of medical informatics and its use cases.

Internet of Medical Things This lecture describes the role of ICT in health-care domain. It outlines the overall health-care ecosystem with ICT technologies. The research trends in health-care domain utilizing ICT technologies, and the state of the art technologies are also highlighted.

Written by Usman Akhtar

Influence of ICT on Medical

This lectures provides insights into Internet of Things (IoT) and its applications in the medical domain. Lecture contents deal with the overall IoT process and discussed in detail different aspects of medical informatics and its use cases.

Internet of Medical Things

This lecture describes the role of ICT in health-care domain. It outlines the overall health-care ecosystem with ICT technologies. The research trends in health-care domain utilizing ICT technologies, and the state of the art technologies are also highlighted.