PhD scholarship: NLP techniques for better access to Electronic Medical Records
L'université de Queensland en Australie
Université étatique, Parcourir ses opportunités similaires
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Université étatique, Parcourir ses opportunités similaires
High quality, efficient healthcare delivery and research rely on easily accessible, accurate, up to date, and holistic information, delivered to the clinicians at the point of care. This project, a collaboration between experienced academic researchers (University of Queensland), clinician-researchers and healthcare providers (Queensland Health, Metro-South and Metro-North Hospital and Health Services), will develop the methods and algorithms to efficiently unlock the rich, generalizable health data in electronic medical records whose extraction is currently prohibitively complex. The student will collaborate with several parties including clinicians, postdocs and senior researchers within the project, and will also held a joint student position at Queensland Health.
The successful applicant will enrol through the School of Information Technology & Electrical Engineering.
Electronic Health Records are stored in structured relational databases comprising of hundreds of tables access to which requires knowledge of the relations and also formulating complex SQL queries. Furthermore, abundant unstructured data (e.g. free text reports) is also not used efficiently. These challenges prohibits the flow of valuable health information to clinicians. This project aims to develop methods to make structured data available in relational databases accessible using NLP and IR methods (e.g. by mapping natural language to SQL). Furthermore, the medical entities mentioned in structured and unstructured data will be recognised (Medical NER) and mapped to their corresponding medical terminologies (e.g. SNOMED CT). The results of this project will be published in top journals and conferences in Natural Language Processing (e.g. ACL, EMNLP), Information Retrieval (e.g. SIGIR, CIKM) and Health Informatics (e.g. AMIA, JAMIA, BMJ BioMed), and will be implemented within Queensland’s iEMR, a state-wide electronic medical records system.. This project will be supervised by Dr. Ash Rahimi and Dr. Guido Zuccon.
To be eligible, you must meet the entry requirements for a higher degree by research.
To be considered for this scholarship, please email the following documents to Dr Ash Rahimi (a.rahimi@uq.edu.au). Please also cc Dr Guido Zuccon (g.zuccon@uq.edu.au)
Please note the following: Submitting the above documents does not constitute a full application for admission into The University of Queensland's PhD program. If you are selected as the preferred applicant, you will then be invited to submit a full application for admission. You can familiarise yourself with the documents required for this process on the Future Student's website.
Applications will be judged on a competitive basis taking into account the applicant’s previous academic record, publication record, honours and awards, and employment history.
A strong background in computer science or relevant fields would be of benefit to someone working on this project.
Previous knowledge and experience in the fields of Natural Language Processing, or Information Retrieval, or Machine Learning or Deep Learning, and hands-on experience with deep learning frameworks (e.g. Tensorflow/Pytorch), and SQL are highly desirable.
Scholarship value : $40,000 per annum, indexed annually. A top-up of $5,000 per annum is also available.
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