Objectives
1. Know the state of the art of applications of information and communication systems and artificial intelligence in terms of health promotion, disease prevention, diagnosis and therapy;
2. Analyze and debate the main ethical, legal and social implications of precision medicine and digital health, namely, the challenges to informed consent, private life, the ownership of biological material and health information, literacy, equity and non-discrimination;
3. Recognize new markets and identify areas of intersection between public health, precision medicine and digital health, namely eHealth and mHealth, biobanks, new digital techniques; devices, big data and machine learning applications;
4. Identify future challenges for health systems and for individual and public health in a new era resulting from digital transformation.
General characterization
Code
531018
Credits
6
Responsible teacher
Professora Doutora Helena Canhão
Hours
Weekly -
Available soon
Total -
Available soon
Teaching language
Portuguese
Prerequisites
Not applicable to
Bibliography
- Varajão J. Arquitectura da gestão de sistemas de informação. FCA Editora de informática, lda. ISBN 972-722-507-1. 2005.
- Weightman, A., Ellis, S., Cullum, A., Sander, L., Turley, R. Grading evidence and recommendations for public health interventions: developing and piloting a framework Health Development Agency, London, 2005.
- Faria, P.L. (Ed.)- The Role of Health Law, Bioethics and Human Rights to Promote a Safer and Healthier World Ed. FLAD e ENSP-UNL, Lisboa, 2006, ISBN 972-98811-4-6
- The Student's Guide to Research Ethics (Open Up Study Skills). Paul Oliver. Open University Press (2003)
- Principles of Biomedical Ethics. Tom L. Beauchamp, James F. Childress. Oxford University Press (2009)
- specified websites.
Teaching method
Teaching methods are differentiated according to the content of each session, with interactive teaching sessions, theoretical-practical analysis, discussion and resolution of case studies. External experts will be invited to present practical examples from their area of expertise. Interaction between students and teachers and interaction between students will be promoted through group work and resolution of pre-programmed challenges.
Evaluation method
The assessment is based on the following parameters and weightings:
a) Degree and quality of participation in classes (20%);
b) appreciation of individual and group work (80%).
Subject matter
1) Digital Health - Concept, Evolution and Perspectives
2) Big data, Large databases, Information Systems and Information Management
3) Telemedicine and telehealth
4) Monitoring and Tele-monitoring systems (sensors, nanotechnology)
5) Artificial Intelligence, Machine Learning and Internet of Things
6) Robotics
7) Anatomical Models and Simulators
8) Medical Devices - Design and implementation
9) Medical Devices - Integration in information networks and clinical perspectives
10) Tissue Engineering, Biocompatibility and Biofabrication of Tissues and Organs
11) Cybersecurity, ethical aspects, confidentiality
12) Patient-Centered Innovation, Entrepreneurship and Transfer to the Market
Programs
Programs where the course is taught:
