Dr Maria Luisa Davila Garcia PhD, MSc AI, BSc
Lecturer in Artificial Intelligence
Summary
Dr. Maria Luisa Davila Garcia has experience working in collaboration with the healthcare sector for nearly 7 years, developing and integrating solutions based on AI. She has expertise in applied AI techniques for medical images, signal analysis, data analysis, pattern recognition, data modelling, data fusion, and image processing.
About
Dr. Maria Luisa Davila Garcia has worked on the analysis of in-vitro live-cell video sequences, using image processing techniques combined with machine learning algorithms in collaboration with the Academic Unit of Reproductive and Developmental Medicine within the Department of Oncology and Metabolism and the Andrology department for Sheffield Teaching Hospitals NHS.
She was involved in the development and implementation of deep learning and transfer learning pipelines to analyse swollen optic nerves, supporting early diagnosis of papilloedema and diabetic retinopathy. The project was a collaboration with the ophthalmologist department supported by Innovate UK. She has been working with applications of image processing techniques for automatic feature extraction of bone area in radiography’s images supporting detection of Skeletal dysplasia condition in children, in collaboration with Paediatric Radiologic from Sheffield Children Hospital/ Medical Research Council MRC.
Collaboration ideas:
- Development of AI solutions to personalised healthcare
- Integration of AI approaches for monitoring, diagnosis, and treatment of health conditions
- Qualitative analysis of health data for knowledge extraction
- Tackling Health Inequalities with AI
- Applied Artificial intelligence in image analysis
Teaching
Subject Area/Group
Games and AI
Courses Taught
MSc Artificial Intelligence
Modules Taught
- Cognitive Systems and Robotics
- Applied Artificial Intelligence
- AI Research and Development Projects
Publications
Conference papers
Garcia, M.L.D., Soto, D.A.P., & Mihaylova, L.S. (2017). A Bag of Features Based Approach for Classification of Motile Sperm Cells. 2017 IEEE International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData). http://doi.org/10.1109/ithings-greencom-cpscom-smartdata.2017.21
Van Raemdonck, L.E.M., Ata-ur-rehman, , Davila-garcia, M.L., Mihaylova, L., Harrison, R.F., & Pacey, A. (2015). An algorithm for Morphological classification of motile human sperm. 2015 Sensor Data Fusion: Trends, Solutions, Applications (SDF). http://doi.org/10.1109/sdf.2015.7347714
Internet Publications
Davila Garcia, M.L., Lanfranchi, V., Offiah, A., Villa-Uriol, M.-.C., & Yang, P. (2021). Image Analysis and Machine Learning for Diagnosis of Skeletal Dysplasias. https://www.researchgate.net/publication/350654682_Image_Analysis_and_Machine_Learning_for_Diagnosis_of_Skeletal_Dysplasias
Other publications
Davila Garcia, M.L., Villa-Uriol, M.-.C., Civaregna, F., Lanfranchi, V., & Haq, I. (2019). "Early detection of Papilloedema and Diabetic Retinopathy". INSIGNEO: https://www.sheffield.ac.uk/insigneo/news/insigneo-showcase-2019