Mary Adewunmi

PhD Student

Qualifications:

Master of Science (Computer Science), Lagos State University, Ojo, Lagos State, Nigeria, 2019; Bachelor of Science (Computer Science), Bowen University, Iwo, Osun State, Nigeria, 2008.

Location:

Darwin – Royal Darwin Hospital Campus

Biography:

Mary Adewunmi is a PhD student and a graduate research assistant at Menzies School of Health Research. She is a group head and founder of research group, Cancer Research with AI (CARESAI). Mary is one of four Global Scholar Committees of the American Association of Cancer Research (GSAC-AACR). Her research focuses on medical use cases with machine/deep learning. Her research on using deep learning for colorectal diagnosis won a GSITA-AACR award in 2022.

Among her multiple grants is the Kaggle-BIPOC 2021 award, along with funding from top AI conferences such as NeurIPS, ICML, and ICLR. Mary is currently a member of the Australian Medical Association (AMA), the American Association for Cancer Research (AACR), the British Association of Cancer Research (BACR), the Data Science Association of Nigeria (DSNAi), the European Association for Cancer Research (EACR), Women in Machine Learning (WiML), the Organisation of Women in Science for the Developing World (OWSD) and Blacks in AI (BAI).

Mary Adewunmi
Email
Research Themes

Clinical decision support system (CDSS) with Machine Learning for Chronic disease

  • A clinical decision support system (CDSS) for medication prescriptions for diabetes patients with large language models (LLM).


 

  1. Adewunmi, M., Sharma, S. K., Sharma, N., Sushma, N. S., & Mounmo, B. (2022). Cancer Health Disparities drivers with BERTopic modelling and PyCaret Evaluation. Cancer Health Disparities, 6. 
  2. Adewunmi, M. A. (2022). Scalable colorectal cancer (CRC) diagnosis model with arterial and unenhanced phases of KRAS mutational status using Apache Spark. Cancer Research, 82(12_Supplement), 6391-6391.
  3.  Abdel-Salam, R., Adewunmi, M., & Akinwale, M. (2024, June). Caresai at semeval-2024 task 2: Improving natural language inference in clinical trial data using model ensemble and data explanation. In Proceedings of the 18th International Workshop on Semantic Evaluation (SemEval-2024) (pp. 1905-1911).
  4. Adewunmi, Mary, Adish Ashraff, Tanya Dixit, Nikhil Shrestha, Veronica Gail Medrano, Bhushan Chougule, Ahmed Fahim, Navaneeth Tirupath, and Sudha Sushma. "JoyBot: RASA-Trained Chatbots to Provide Mental Health Assistance for Australians." (2022).
  5. Hamnett, L., Adewunmi, M., Abayomi, M., Raheem, K., & Ahmed, F. (2023). Enhancing Transformer-Based Segmentation for Breast Cancer Diagnosis using Auto-Augmentation and Search Optimisation Techniques. arXiv preprint arXiv:2311.11065.
  6.  Adeyemo, O. M., Ashimiyu‐Abdusalam, Z., Adewunmi, M., Ayano, T. A., Sohaib, M., & Abdel‐Salam, R. (2024). Network‐based identification of key proteins and repositioning of drugs for non‐small cell lung cancer. Cancer Reports, 7(4), e2031.
  7. Sohaib, M., & Adewunmi, M. (2023). Artificial intelligence-based prediction on lung cancer risk factors using deep learning. arXiv preprint arXiv:2304.05065.
  8. Oveh, R. O., Adewunmi, M. A., & Aziken, G. O. (2022, November). BERTopic Modelling with P53 in Ovarian Cancer. In 2022 5th Information Technology for Education and Development (ITED) (pp. 1-4). IEEE.
     
Find these publications at Pubmed or visit our Publications Library