Health Informatics

Teacher(s)

Jodogne Sébastien;

Language

English
> French-friendly

Prerequisites

Students are expected to master the following skills:

• Develop in the Python language.
• Implement and test a solution in the form of a software prototype.
• Demonstrate a good understanding of the basic concepts and the methodology of programming.
• Analyze a problem to provide an IT solution and implement it in a high-level programming language.

These skills are for instance covered in courses LEPL1401, LEPL1402, LINFO1101, LSINC1101 and LSINC1402.
Database and network programming skills (as covered for instance in LEPL1509 and LSINC1509) are also useful but will be briefly reviewed in LINFO2381.

Main themes

• Medical information systems and associated medical devices.
• International medical interoperability standards and clinical nomenclatures.
• Document-oriented databases.
• Health IT networks and associated network protocols.
• Management and analysis of patient data, including through machine learning.

Learning outcomes

At the end of this learning unit, the student is able to :

With respect to the AA referring system defined for the “Master in computer science and engineering” (INFO2M), the course contributes to the development, mastery, and assessment of the following skills: AA1.1, AA1.2 AA2.3, AA2.4 AA3.1 AA5.2, AA5.4 AA6.2, AA6.4, AA6.5 With respect to the AA referring system defined for the “Master in computer science” (SINF2M), the course contributes to the development, mastery, and assessment of the following skills: AAM3 AA2.3, AA2.4 AA3.1 AA4.3 AA5.2, AA5.4 AA6.2, AA6.4, AA6.5 With respect to the AA referring system defined for the “Master in biomedical engineering” (GBIO2M), the course contributes to the development, mastery, and assessment of the following skills: AA1.1, AA1.2 AA2.3, AA2.4 AA3.1 AA4.3 AA5.2, AA5.4 AA6.2, AA6.4, AA6.5 With respect to the AA referring system defined for the “Master in data science engineering” (DATE2M), the course contributes to the development, mastery, and assessment of the following skills: AA1.4, AA1.6 AA2.3, AA2.4 AA3.1 AA4.3 AA5.2, AA5.4 AA6.2, AA6.4, AA6.5 With respect to the AA referring system defined for the “Master in data science: Information technology” (DATI2M), the course contributes to the development, mastery, and assessment of the following skills: AA1.4, AA1.6 AA2.3, AA2.4 AA3.1 AA4.3 AA5.2, AA5.4 AA6.2, AA6.4, AA6.5 Students completing successfully this course should be able to: understand the digital environment used in the global healthcare context; design and develop software that is interoperable with existing medical information systems; identify paradigms for developing new IT applications aimed at a clinical department, a medical institution, or a healthcare network. Students will have developed skills and operational methodology. They will notably have developed their ability to: integrate into a multidisciplinary approach between computer science and medicine, using wisely the terminology, standards, tools, and existing methods; make the best use of available time to successfully carry out small-scale projects.

Content

• Medical information systems and associated medical devices.
• International medical interoperability standards (HL7, FHIR, DICOM...) and clinical nomenclatures (SNOMED-CT, LOIC...).
• Document-oriented databases (NoSQL).
• Health IT networks and associated network protocols.
• Management and analysis of patient data, including through machine learning.
• Historical perspective on the development of medical informatics.

Teaching methods

• Lectures in auditorium.
• Continuous assessment:
  • Individual practical Python programming exercises to be completed on the INGInious platform.
  • In addition to the programming exercises, additional assignments may be required.
• A teaching assistant will be available to answer questions about the exercises and assignments during the practical sessions scheduled in the timetable.

Evaluation methods

In the first session, the exam will be held in person and on site, in written form and without access to course materials, with open-ended questions. The assessment covers all the material covered in lectures, practical exercises, and additional assignments. The final grade is calculated as a weighted average of the exam (80%) and continuous assessment (20%). If students re-enroll in the course in the following academic year, the exercises and assignments must be completed again in full.
In the second session, the exam will be oral, in person and on site. Continuous assessment no longer counts in the second session; the oral exam therefore accounts for 100% of the grade.
In both the first and second sessions, the exam questions will be provided in English, and answers may be given either in English or in French.
Continuous assessment consists of the practical exercises and additional assignments, which are weighted equally. They result in a single overall grade, communicated after the final session. Failure to comply with the methodological guidelines provided by the instructor, particularly regarding the use of online resources, plagiarism, or collaboration between students on an exercise, will result in an overall grade of 0 for the continuous assessment.
In particular, the use of generative AI tools and any form of collaboration is strictly prohibited during the exercises and assignments. The use of public resources intended for programmers (e.g., stackoverflow.com) is permitted, provided that each piece (or fragment) of code submitted by the student mentions all the resources used. The distribution or exchange of code (or code fragments) between students is not permitted by any means whatsoever (e.g., GitHub, Facebook, Discord, etc.), even after the submission deadline for the exercises and assignments.

Online resources

Moodle UCLouvain -> https://moodle.uclouvain.be/course/view.php?id=8597

Teaching materials

• Les transparents présentés lors des exposés théoriques, de même que les notes relatives aux séances de cours et quelques références bibliographiques, sont disponibles sur Moodle.
• The slides presented during the theoretical lectures, as well as the course notes and some bibliographical references, are available on Moodle.

Faculty or entity

> INFO