The application of Artificial Intelligence in Pathology Research to discover, develop, validate and deliver novel diagnostics

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Studentship Strategic Priority Area:Industrial Collaborative ResearchKeywords: Digital Pathology, Artificial Intelligence, Subtyping, Colorectal CancerThe integration of digital technology within Histopathology has facilitated the transfer of valuable image-rich data for the purposes of diagnosis, education and research and will undoubtedly further enable precision medicine.Over recent years, there has been a drive to incorporate quantitative analysis processes into these platforms so that morphological information can be converted into quantitative data, for research and clinical applications. Artificial Intelligence (AI), which involves the utilization of deep learning technologies, has recently been integrated within existing digital pathology platforms. This provides a unique opportunity to utilize image analysis, with AI, as a quantitative digital tool, to assist Pathologists in the complex interpretations of tissue-based sections. This brings the potential to contribute to consistency in diagnosis, assimilate 'big data' to permit early detection of minor changes associated with disease processes and, in conjunction with companion diagnostics, enable patient stratification for predicting response to therapies.The aim of the project is for a biomedical scientist or biologist to work closely with the Pathology group and Edwards group in Institute of Cancer Sciences University of Glasgow and OracleBio Ltd, a leading industry-based pathology imaging solutions company, to leverage research using AI to not only determine its value and impact for future pathology investigations and research, but also to assist in the implementation of a novel predictor in gastrointestinal cancer. It is expected that the student will spend up to 50% of their time at OracleBio Ltd. OracleBio will provide image analysis platforms, including AI algorithms, and the support of industry leading quantitative tissue-based expertise.The project will enable development of knowledge of disease processes, histopathology tissue recognition, application of molecular techniques and computer science algorithms used on digital image analysis platforms, within wider research and development and commercial contexts.