Medical analytics for healthcare intelligence – Recent advances and future directions
File version
Author(s)
Keravnou-Papailiou, E
Antoniou, G
Griffith University Author(s)
Primary Supervisor
Other Supervisors
Editor(s)
Date
Size
File type(s)
Location
License
Abstract
Recent advances in information technology have facilitated the massive collection of big data in numerous areas, including the healthcare sector. Healthcare data exists in various forms that can be briefly grouped into two categories. First, there is clinical data that is directly related to patients and medical conditions. This data includes, but is not limited to, demographic data, patient history, lab test results, physical examinations, diagnostic analysis and medical notes. The proliferation of wearable devices also enables the collection of clinical data periodically through monitoring systems via wireless technology, which supports the real-time tracking of patient care and timely adjustment of treatment plans. A second category of healthcare data originates from the business side of healthcare, such as operational and equipment costs, and logistic and administrative data which may be utilised for the optimisation of operational dynamics to support effective healthcare services and generally enhance utility in medical practice.
Journal Title
Artificial Intelligence in Medicine
Conference Title
Book Title
Edition
Volume
112
Issue
Thesis Type
Degree Program
School
Publisher link
Patent number
Funder(s)
Grant identifier(s)
Rights Statement
Rights Statement
Item Access Status
Note
Access the data
Related item(s)
Subject
Engineering
Information and computing sciences
Persistent link to this record
Citation
Chen, T; Keravnou-Papailiou, E; Antoniou, G, Medical analytics for healthcare intelligence – Recent advances and future directions, Artificial Intelligence in Medicine, 2021, 112, pp. 102009