2024
Digital Health
Name: Digital Health
Code: CMS13723D
6 ECTS
Duration: 15 weeks/156 hours
Scientific Area:
Health Sciences
Teaching languages: Portuguese
Languages of tutoring support: Portuguese
Presentation
This UC aims to understand 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, main ethical, legal and social implications of medicine in need and digital health.
Sustainable Development Goals
Learning Goals
-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.
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.
Contents
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
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
Teaching Methods
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.
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 (50%); c) individual written exam (30%).
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.
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 (50%); c) individual written exam (30%).
Certificações
