BIG DATA AND THE INTERNET OF MEDICAL THINGS

DIG5BDM

2020

Credit points: 15

Subject outline

The volume of health data isincreasing exponentially in the digital age, providing more data for healthmanagement and research. In this subject you will gain an understanding of what#big data# is, why it is important to the health and healthcare sectors, andhow it can be used in real-world applications. You will explore therequirements for research infrastructure, review the current big data landscape(including assets, facilities and services) and investigate the requirementsaround information security in relation to big data in digital health. Data linkage techniques and various strategies to tackle problems relating todata linkage quality will be explored and you will investigate how the Internetof Medical Things (IoMT) can benefit health research using compatible devices,apps and research platforms. You will develop a working knowledge of theanalytical techniques used to mine big data including machine learning,predictive analytics, forecasting, visualisation, simulation and complex eventprocessing for use in healthcare and in public health.

SchoolSchool of Psychology & Public Health

Credit points15

Subject Co-ordinatorJames Boyd

Available to Study Abroad StudentsYes

Subject year levelYear Level 5 - Masters

Exchange StudentsYes

Subject particulars

Subject rules

Prerequisites None

Co-requisites None

Incompatible subjects None

Equivalent subjects None

Special conditions None

Readings

Resource TypeTitleResource RequirementAuthor and YearPublisher
ReadingsMedical Internet of Things and Big Data in HealthcareRecommendedDimiter DimitrovHealthcare informatics research. 2016 Jul 1;22(3):156-63.
ReadingsThe Medical Futurist (https://medicalfuturist.com)RecommendedBertalan Meskó, Nóra Radó, et al.The Medical Futurist
ReadingsMedical Big Data and Internet of Medical Things # Advances, Challenges and ApplicationsPrescribedAboul Ella Hassanien, Nilanjan Gey, Surekha Borra (2018)CRC Press

Graduate capabilities & intended learning outcomes

01. Appraise the role of Big Data in health and the Internet of Medical Things and their impacts on healthcare provision.

Activities:
Lectures, Seminar presentations, case studies, workshops/tutorials

02. Critically analyse and interpret results from Big Data analytic information.

Activities:
Lectures, Seminar presentations, case studies, workshops/tutorials

03. Evaluate the requirements for research platforms that house and use Big Data and data from the Internet of Medical Things.

Activities:
Lectures, Seminar presentations, case studies, workshops/tutorials

04. Evaluate opportunities for data sharing and the Internet of Medical Things to provide solutions for real-world problems.

Activities:
Seminar presentations, case studies, workshops/tutorials

05. Assess and predict data integrity issues, technical and legislative challenges of data integration for the application of Big Data in the health system.

Activities:
Lectures, Seminar presentations, case studies, workshops/tutorials

Subject options

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Start date between: and    Key dates

Melbourne, 2020, LTU Term 4, Blended

Overview

Online enrolmentYes

Maximum enrolment size60

Enrolment information Priority given to Master of Digital Health and Graduate Certificate of Digital Health students then to all other courses by order of enrolment Merit based quota management

Subject Instance Co-ordinatorJames Boyd

Class requirements

Unscheduled Online Class Week: 30 - 35
Two 1.5 hours unscheduled online class per week on weekdays during the day from week 30 to week 35 and delivered via online.

Scheduled Online Class Week: 30 - 35
Two 2.0 hours scheduled online class per week on weekdays during the day from week 30 to week 35 and delivered via online.

Assessments

Assessment elementComments% ILO*
Oral Presentation/Seminar (1500-word equivalent)~30 min presentation20 01, 03, 05
Big Data Assignment (3000-word equivalent)Individual essay, review, report, etc.50 02, 04
Group project and presentation (2000-word equivalent per student)Project (1250-word equivalent) and ~15 mins presentation (750-words)30 02, 03, 05

Melbourne, 2020, LTU Term 6, Blended

Overview

Online enrolmentYes

Maximum enrolment size60

Enrolment information Priority given to Master of Digital Health and Graduate Certificate of Digital Health students then to all other courses by order of enrolment Merit based quota management

Subject Instance Co-ordinatorJames Boyd

Class requirements

Unscheduled Online Class Week: 45 - 50
Two 1.5 hours unscheduled online class per week on weekdays during the day from week 45 to week 50 and delivered via online.

Scheduled Online Class Week: 45 - 50
Two 2.0 hours scheduled online class per week on weekdays during the day from week 45 to week 50 and delivered via online.

Assessments

Assessment elementComments% ILO*
Oral Presentation/Seminar (1500-word equivalent)~30 min presentation20 01, 03, 05
Big Data Assignment (3000-word equivalent)Individual essay, review, report, etc.50 02, 04
Group project and presentation (2000-word equivalent per student)Project (1250-word equivalent) and ~15 mins presentation (750-words)30 02, 03, 05