BIG DATA AND THE INTERNET OF MEDICAL THINGS

DIG5BDM

2021

Credit points: 15

Subject outline

The volume of health data is increasing exponentially in the digital age, providing more data for health management 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, and how it can be used in real-world applications. You will explore the requirements for research infrastructure, review the current big data landscape(including assets, facilities and services) and investigate the requirements around information security in relation to big data in digital health. Data linkage techniques and various strategies to tackle problems relating to data linkage quality will be explored and you will investigate how the Internet of Medical Things (IoMT) can benefit health research using compatible and research platforms. You will develop a working knowledge of the analytical techniques used to mine big data including machine learning, predictive analytics, forecasting, visualisation, simulation and complex event processing for use in healthcare and in public health.

SchoolPsychology and Public Health

Credit points15

Subject Co-ordinatorJames Boyd

Available to Study Abroad/Exchange StudentsYes

Subject year levelYear Level 5 - Masters

Available as ElectiveNo

Learning ActivitiesN/A

Capstone subjectNo

Subject particulars

Subject rules

Prerequisites None

Co-requisitesN/A

Incompatible subjectsN/A

Equivalent subjectsN/A

Quota Management StrategyMerit based quota management

Quota-conditions or rulesN/A

Special conditionsN/A

Minimum credit point requirementN/A

Assumed knowledgeN/A

Readings

Medical Internet of Things and Big Data in Healthcare

Resource TypeRecommended

Resource RequirementN/A

AuthorDimiter Dimitrov

Year2016

Edition/VolumeN/A

PublisherHealthcare informatics research. 2016 Jul 1;22(3):156-63.

ISBNN/A

Chapter/article titleN/A

Chapter/issueN/A

URLN/A

Other descriptionN/A

Source locationN/A

Medical Big Data and Internet of Medical Things Advances, Challenges and Applications

Resource TypePrescribed

Resource RequirementN/A

AuthorAboul Ella Hassanien, Nilanjan Gey, Surekha Borra

Year2018

Edition/VolumeN/A

PublisherCRC Press

ISBNN/A

Chapter/article titleN/A

Chapter/issueN/A

URLN/A

Other descriptionN/A

Source locationN/A

The Medical Futurist

Resource TypeRecommended

Resource RequirementN/A

AuthorBertalan Meskó, Nóra Radó, et al.

YearN/A

Edition/VolumeN/A

PublisherThe Medical Futurist

ISBNN/A

Chapter/article titleN/A

Chapter/issueN/A

URLhttps://medicalfuturist.com

Other descriptionN/A

Source locationN/A

Career Ready

Career-focusedNo

Work-based learningNo

Self sourced or Uni sourcedN/A

Entire subject or partial subjectN/A

Total hours/days requiredN/A

Location of WBL activity (region)N/A

WBL addtional requirementsN/A

Graduate capabilities & intended learning outcomes

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.
02. Critically analyse and interpret results from Big Data analytic information.
03. Evaluate the requirements for research platforms that house and use Big Data and data from the Internet of Medical Things.
04. Evaluate opportunities for data sharing and the Internet of Medical Things to provide solutions for real-world problems.
05. Assess and predict data integrity issues, technical and legislative challenges of data integration for the application of Big Data in the health system.

Subject options

Select to view your study options…

Start date between: and    Key dates

Melbourne (Bundoora), 2021, LTU Term 4, Online

Overview

Online enrolmentYes

Maximum enrolment size60

Subject Instance Co-ordinatorJames Boyd

Class requirements

Lecture/SeminarWeek: 30 - 35
Two 1.50 h lecture/seminar per week on weekdays during the day from week 30 to week 35 and delivered via online.

WorkShopWeek: 30 - 35
Two 2.00 h workshop per week on weekdays during the day from week 30 to week 35 and delivered via online.

Assessments

Assessment elementCommentsCategoryContributionHurdle% ILO*
Oral Presentation/Seminar (1500-word equivalent) ~30 min presentationN/AN/AN/ANo20 SILO1, SILO3, SILO5
Big Data Assignment (3000-word equivalent) Individual essay, review, report, etc.N/AN/AN/ANo50 SILO2, SILO4
Group project and presentation (2000-word equivalent per student) Project (1250-word equivalent) and ~15 mins presentation (750-words)N/AN/AN/ANo30 SILO2, SILO3, SILO5

Melbourne (Bundoora), 2021, LTU Term 6, Online

Overview

Online enrolmentYes

Maximum enrolment size60

Subject Instance Co-ordinatorJames Boyd

Class requirements

Lecture/SeminarWeek: 45 - 50
Two 1.50 h lecture/seminar per week on weekdays during the day from week 45 to week 50 and delivered via online.

WorkShopWeek: 45 - 50
Two 2.00 h workshop per week on weekdays during the day from week 45 to week 50 and delivered via online.

Assessments

Assessment elementCommentsCategoryContributionHurdle% ILO*
Oral Presentation/Seminar (1500-word equivalent) ~30 min presentationN/AN/AN/ANo20 SILO1, SILO3, SILO5
Big Data Assignment (3000-word equivalent) Individual essay, review, report, etc.N/AN/AN/ANo50 SILO2, SILO4
Group project and presentation (2000-word equivalent per student) Project (1250-word equivalent) and ~15 mins presentation (750-words)N/AN/AN/ANo30 SILO2, SILO3, SILO5