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Database and Machine Learning - Querying Forensic, Clinical, and Medical Databases

Primary supervisor

David Taniar

Co-supervisors

  • Vincent Lee
  • Assoc. Prof. Richard Bassed (Victorian Institute of Forensic Medicine - VIFM)

Would you like to use your Database and ML knowledge to solve real-world problems in medicine (e.g. clinical and forensic medicine)? Forensic and clinical databases actually consists of many different data storage systems. For example, Xray and CT scan are stored in one system; hospital reports in another system; pathological data in a different system; patient records or Electronic Medical Records (EMR) are in another system... They are disaggregated in many places. 

It is very often that a clinician, after seeing a case (or a patient), would remember that he/she had seen or vaguely remembers a similar case (or cases) in the past (e.g. e few years ago), but could not recall the case(s). When this happens, the clinician needs to manually search the data in various places. This project aims to assist clinicians to efficiently search the data from these database. Retrieving similar past cases is important in the medical domain. The project will utilise ML techniques to pre-cluster data, and build an interface for clinician to query the database. 

Required knowledge

You must have a strong database background, together with Machine Learning skills. Knowledge on web search techniques and indexing would be beneficial.