Back Module: SBI122

Clinical and Scientific Computing for the Physical Sciences 2

Module information

Module details

Title
Clinical and Scientific Computing for the Physical Sciences 2
Type
Specialist
Module code
SBI122
Credits
30
Requirement
Compulsory

Aim of this module

This module provides the trainee with the knowledge that underpins the specialist rotations in the work based learning programme.

Advanced Information and communications technology Skills

To ensure that the trainee can apply Information and communications technology (ICT) hardware and software solutions safely within a clinical environment.

Database Management, Data Mining and Modelling

It will enable the trainee to design and develop a database, undertake data mining using a large data set, summarise and present the data, and develop models for biological systems.

Work-based components

Submodules

Code Title Action
SBI122c1 Advanced Information and communications technology Skills View
SBI122c2 Database Management, Data Mining and Modelling View

Academic content (MSc in Clinical Science)

Important information

The academic parts of this module will be detailed and communicated to you by your university. Please contact them if you have questions regarding this module and its assessments. The module titles in your MSc may not be exactly identical to the work-based modules shown in the e-portfolio. Your modules will be aligned, however, to ensure that your academic and work-based learning are complimentary.

Learning outcomes

  1. Develop web-based solutions in a complex networking environment.
  2. Use a range of complex software techniques to solve clinical problems.
  3. Discuss and evaluate the range of issues encountered in the development of novel software engineering solutions in medicine.
  4. Critically evaluate computer models for biological systems.

Indicative content

Project management

  • Risk management
  • Team management (personnel and technical)
  • Project planning (resource and technical)
  • Education and training
  • Cost estimation
  • Project scheduling

Hosting environments

  • Storage services
    • Backup, Archiving, Business Continuity & Disaster Recovery
    • RAID, SAN
  • Server virtualisation
  • Cloud computing
  • Web services (SOAP & REST)
  • Security and governance for cloud services

 Networking

  • Local and wide area networking, including:
    • Available architectures
    • Performance issues
    • Scalability
    • Bridging versus routing
    • Cabling infrastructure
    • Hubs
    • Traffic management
  • Data Exchange Protocols
  • Data exchange standards – Digital Imaging and Communications in Medicine (DICOM) and Healthcare Level 7 (HL7)
  • Links to hospital administration systems

Software techniques

  • Neural networks and their applications
  • Artificial intelligence and expert systems
  • Image processing software, including image reconstruction and registration
  • Finite element analysis
  • Genetic algorithms

Database management and data mining

  • The relational model of data
  • Implementation of relational databases
  • Advanced SQL programming
  • Query optimisation
  • Concurrency control and transaction management
  • Database performance tuning
  • Distributed relational systems and data replication
  • Columnstore/data warehousing database engines
  • Document-oriented databases (e.g. Lucene)
  • Security considerations
  • Data mining
  • Large data set methodologies
  • Database standards and standards for interoperability and integration
  • Data analysis and presentation

Modelling biological systems

  • Analysis of DNA, protein, biological diversity and molecular interaction data
  • Use of bioinformatics and systems biology databases
  • Data sources and data synthesis.
  • Detailed knowledge and understanding of algorithms in bioinformatics and theoretical systems biology.
  • Monte-Carlo modelling
  • Compartmental modelling

Clinical experiences

Important information

Clinical experiential learning is the range of activities trainees may undertake in order to gain the experience and evidence to demonstrate their achievement of module competencies and assessments. The list is not definitive or mandatory, but training officers should ensure, as best training practice, that trainees gain as many of these clinical experiences as possible. They should be included in training plans, and once undertaken they should support the completion of module assessments and competencies within the e-portfolio.

Activities

Advanced Information and communications technology Skills

  • Critically review one or more existing systems for compliance with Information Governance Toolkit.
  • Work with colleagues on the deployment and management of ICT systems within the Physical Sciences.
  • Support clinical colleagues in the integration of ICT systems, such as the integration of medical devices into patient management systems.
  • Undertake the administration of a local area network (user specification; initial set-up; shared resources; security issues, resilience and data backup and retrieval).
  • Work within clinical teams and clinical settings using ICT as part of routine service and service development, and critically evaluate the current and future role of ICT from the perspective of the patient, patient safety, the department and the healthcare organisation.

Database Management, Data Mining and Modelling 

  • Observe a range of large databases/data sets in use in the hospital setting and critically evaluate their use in discussions with your training officer.
  • Work with a clinical team to specify and implement a relational database.
  • Observe the use of large data sets to inform clinical care through the use of data mining techniques.
  • Work with a large data set to summarise and present the outcome of data mining to colleagues.
  • Work with a clinical team to develop a computational model of a biological or physiological system using, for example Monte Carlo, pharmacokinetic modelling, neural networks, or finite element analysis.
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