Study-Unit Description

Study-Unit Description


TITLE Medical Informatics

LEVEL 05 - Postgraduate Modular Diploma or Degree Course


DEPARTMENT Computer Information Systems

DESCRIPTION This study-unit introduces several topics, including:

- An introduction to medical informatics (including clinical informatics and public health informatics);
- Medical image processing principles and techniques including magnetic resonance imaging (MRI), functional MRI (fMRI), nuclear MRI, diffusion MRI, electrocardiography (ECG), electroencephalography (EEG), magnetoencephalography (MEG) and others;
- Brain computer interface (BCI);
- Clinical decision support systems (CDSS) including knowledge based CDSS, non-knowledge based (evidence based) CDSS;
- Information management in health and social care (including hospital databases and electronic patient records, characterizing admission and discharge patterns, resource requirements forecasting and allocation and budgetary analysis);
- Handling missing data (including missing data analysis methods and tools);
- Ambient assisted living and tele-medicine (including smart homes, remote patient monitoring and sensor networks, analysis and interpreting of sensor data);
- Genomics data, gene expression images, genomics data analysis and genomic data mining;
- Text mining in medicine (including medical ontologies, semantic interpretation in medicine, semantic text parsing for patient records, IBM-Watson and its application in medical informatics).

Study-unit Aims:

This study-unit helps students to prepare for a career in Medical Informatics. It introduces some of the biomedical problem areas, which can potentially be tackled through machine learning and digital signal processing. The emphasis would be on analysing how these techniques can be used to process biomedical information and solve related issues. The topics listed above are for guidance only. New topics can be added or some topics might be omitted based on interest and latest developments in the field.

Learning Outcomes:

1. Knowledge & Understanding:
By the end of the study-unit the student will be able to:

- Describe some of the biomedical problem areas which have potential of applications of machine learning and digital signal processing;
- Analyse issues in the biomedical domain and how these can be tackled via machine learning and digital signal processing;
- Describe how machine learning can help improving decision making and process control in biomedicine.

2. Skills:
By the end of the study-unit the student will be able to:

- Analyse biomedical problem areas which have potential of applications of machine learning and digital signal processing;
- Apply appropriate machine learning methods to develop solutions and tools to help processing biomedical information to improve decision-making and process control in biomedicine.

Main Text/s and any supplementary readings:

Main Text/s:

- Medical Informatics: Knowledge Management and Data Mining in Biomedicine, by Hsinchun Chen, Springer, 19 Jul 2006.
- Principles of Biomedical Informatics, by Ira J. Kalet Academic Press; 2nd edition (13 Nov 2013), ISBN: 9780124160194.

Supplementary readings:

- Biomedical Informatics: Computer Applications in Health Care and Biomedicine (Health Informatics), by Edward H. Shortliffe (Editor), James J. Cimino (Editor), Springer; 4th ed. 2014 edition (December 20, 2013).
- Applied Medical Image Processing: A Basic Course by Wolfgang Birkfellner, CRC Press, September 17, 2010, SBN: 978- 1439824443.
- Advances in Intelligent Analysis of Medical Data and Decision Support Systems, by Kountchev, Roumen; Iantovics, Barna (Eds.), Springer; 2013 edition (May 31, 2013), ISBN: 978-3319000282.
- Wireless Technologies for Ambient Assisted Living and Healthcare: Systems and Applications by Athina Lazakidou, Konstantinos Siassiakos and Konstantinos Ioannou, Inf. Science Pub, 2010.
- Unified modelling for Care of the Elderly, by Dr Lalit Garg, PhD thesis, University of Ulster, UK.

STUDY-UNIT TYPE Lecture, Independent Study and Project

Assessment Component/s Assessment Due Resit Availability Weighting
Assignment SEM2 Yes 50%
Online Examination (1 Hour and 30 Minutes) SEM2 Yes 50%


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The availability of optional units may be subject to timetabling constraints.
Units not attracting a sufficient number of registrations may be withdrawn without notice.
It should be noted that all the information in the description above applies to study-units available during the academic year 2020/1. It may be subject to change in subsequent years.