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  Advancing Diagnostic Radiology through Artificial Intelligence and Machine Learning

   Cardiff School of Computer Science & Informatics

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  Dr Hantao Liu, Dr P Corcoran, Dr Wei Zhou  No more applications being accepted  Competition Funded PhD Project (Students Worldwide)

About the Project

Often, the efficacy of disease treatments relies heavily on the accurate interpretation of radiological imaging by medical professionals. However, diagnosing pathologies from medical images presents significant challenges. Even experienced radiologists are prone to misdiagnoses due to the inherent complexity of medical imaging.

It would be beneficial for image readers to utilise artificial intelligence (AI) and machine learning (ML) tools to aid in the interpretation task. These tools could help radiologists mitigate the inherent limitations of human perception and bias, potentially leading to a reduction in diagnostic errors. More broadly, this technological advancement could have far-reaching implications, improving healthcare delivery across a wide range of clinical settings.

The objectives of this project include collecting high-quality, anonymised datasets comprising image-based diagnoses in collaboration with practicing radiologists; and developing AI/ML algorithms capable of automatically generating decision-making outcomes relevant to clinical radiology. The overarching goal is to use these AI/ML algorithms to support radiologists to improve diagnostic accuracy and efficiency, ultimately enhancing patient outcomes. Furthermore, these tools have the potential to extend diagnostic support to underserved regions where access to radiologists may be limited.

The project will be conducted within the internationally recognised Visual Computing Research Group at Cardiff University, with support from the Department of Clinical Radiology at the University Hospital of Wales and Great Ormond Street Hospital for Children, NHS Foundation Trust.

Contact for information on the project: Professor Hantao Liu ([Email Address Removed])

Academic criteria: A 2:1 Honours undergraduate degree or a master's degree, in computing or a related subject. Applicants with appropriate professional experience are also considered.

Applicants for whom English is not their first language must demonstrate proficiency by obtaining an IELTS score of at least 6.5 overall, with a minimum of 6.0 in each skills component.

How to apply:

Please contact the supervisors of the project prior to submitting your application to discuss and develop an individual research proposal that builds on the information provided in this advert. Once you have developed the proposal with support from the supervisors, please submit your application following the instructions provided below

Please submit your application before the application deadline (6th May 2024) via Computer Science and Informatics - Study - Cardiff University

In order to be considered candidates must submit the following information:

·       Supporting statement

·       CV

·       In the ‘Research Proposal’ section of the application enter the name of the project you are applying to and upload your Individual research proposal, as mentioned above in BOLD

·       In the funding field of your application, insert “I am applying for 2024 PhD Scholarship in Computer Science and Informatics”, and specify the project title and supervisors of this project in the text box provided.

·       Qualification certificates and Transcripts

·       References x 2

·       Proof of English language (if applicable)

If you have any questions on the application process, please contact [Email Address Removed]

Computer Science (8)

Funding Notes

A School-Funded PhD Scholarship is available for entry 2024/25.
In the Funding field of your application, insert "I am applying for 2024 PhD Scholarship" and specify the project title and supervisor of this project in the fields provided. This project is also open to Self-Funded students worldwide. If you are interested in applying for a Self-Funded PhD, please search FindAPhD for this specific project title.


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