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Clinical Decision Support Systems

Code: IM2014_06     Acronym: SADC

Classification Keyword
OFICIAL Medical Informatics

Instance: 2020/2021 - 2S (of 08-02-2021 to 30-07-2021) Ícone do Moodle

Active? Yes
Responsible unit: Departamento de Medicina da Comunidade, Informação e Decisão em Saúde
Course/CS Responsible: Master Programme in Medical Informatics

Cycles of Study/Courses

Acronym No. of Students Study Plan Curricular Years Credits UCN Credits ECTS Contact hours Total Time
MIM 21 Plano Oficial (Atualizado Despacho n.º 5137/2020) 1 - 6 55 162

Teaching Staff - Responsibilities

Teacher Responsibility
Pedro Pereira Rodrigues
Inês de Castro Dutra

Teaching - Hours

Theoretical and practical : 2,14
Tutorial Supervision: 1,43
Others: 0,36
Type Teacher Classes Hour
Theoretical and practical Totals 1 2,14
Pedro Pereira Rodrigues 1,07
Inês de Castro Dutra 1,07
Tutorial Supervision Totals 1 1,43
Inês de Castro Dutra 0,714
Pedro Pereira Rodrigues 0,714
Others Totals 1 0,36
Inês de Castro Dutra 0,178
Pedro Pereira Rodrigues 0,178

Teaching language



The main objective of this discipline is to provide necessary and general concepts of clinical decision support systems to students.

Learning outcomes and competences

      Define strategies for clinicial decision support;

● Define strategies for clinicial decision support; 
● Identify models for the clinical decision support;
● Interpret and evaluate classic clinical decision support systems;
● Interpret and evaluate advanced clinical decision support systems;
● Design, implement and evaluate clinical decision support systems;
● Develop critical thinking.

Working method



Deduction, Induction and the process of clinical decision support
Forms of Knoweldge Representation
Examples of clinical decision support systems
Development, implementation and evaluation of strategies for decision support
Medical Guidelines to support clinical decision
Algorithms for clinical decision support
Reasoning with uncertainty
Machine learning for clinical decision support
Interpretation and evaluation of clinical decision support models

Mandatory literature

E. Berner; Clinical decision support systems: theory and practice, Springer, 2006 (ISBN 0387339140)
Robert A. Greenes; Clinical Decision Support: The Road Ahead (ISBN-10: 0123693772)
Jerome A. Osheroff, Jonathan M. Teich, Donald Levick, Luis Saldana, Ferdinand T. Velasco, Dean F. Sittig, Kendall M. Rogers and Robert A. Jenders; Improving Outcomes with Clinical Decision Support: An Implementer’s Guide, HIMMS
S. Brahnam, L.C. Jain (Eds.); Advanced Computational Intelligence Paradigms in Healthcare 5, 2011 (ISBN 978-3-642-16094-3)
P. Lucas, J.A. Gámez, A. Salmerón Cerdan (Eds.); Advances in Probabilistic Graphical Models, 2007 (ISBN 978-3-642-08854-4)
M. Schmitt, H.-N. Teodorescu, A. Jain, A. Jain, S. Jain (Eds.); Computational Intelligence Processing in Medical Diagnosis, 2002 (ISBN 978-3-7908-1463-7)

Teaching methods and learning activities

Teaching methodologies: Theorectical classes about the topics. Practical classes to solve basic and more complex problems in clinical decision.
Evaluation methodologies: Final exam (12 points) and group assignment (8 points).

Evaluation Type

Distributed evaluation with final exam

Assessment Components

Designation Weight (%)
Exame 60,00
Trabalho escrito 40,00
Total: 100,00

Amount of time allocated to each course unit

Designation Time (hours)
Apresentação/discussão de um trabalho científico 25,00
Estudo autónomo 60,00
Frequência das aulas 30,00
Trabalho escrito 47,00
Total: 162,00

Eligibility for exams

Delivery of an assignment during the evaluation process.

Calculation formula of final grade

Evaluation methodologies: Final exam (10 points), group assignment (7 points) and individual assignments along the curricular unit (3 valores)
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