Dr. Michela Antonelli

Instructor

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Biography

Michela Antonelli is a Lecturer in Health Data Mining at King's College London. Her research focuses on leveraging advancements in artificial intelligence for healthcare, particularly in the area of cancer imaging epidemiology. She has a strong background in computer engineering and AI, contributing to innovative applications in prostate cancer diagnosis. Dr. Antonelli's work has provided significant insights into the impact of the COVID-19 pandemic on healthcare policy, both nationally and internationally. Prior to her current role, she was a senior research fellow at University College London, where she developed state-of-the-art methods for zonal prostate segmentation. At King's College London, she leads the Prostate Cancer Pathway at the London Medical Imaging AI Centre and is a part of the Value-Based Healthcare initiative at the new Centre for Ageing Resilience in Changing Environments (CARICE). With over 20 years of experience applying AI to solve real-world problems, particularly in healthcare, her expertise includes advanced image analysis, big data, and deep learning techniques within medical imaging. Dr. Antonelli has published more than 50 journal articles indexed in PubMed, garnering over 10,000 citations. She teaches courses in Object-Oriented Programming and Machine Learning for Biomedical Applications, contributing to the education of future practitioners in the field.

Research Interests

Courses

Object-Oriented Programming Machine Learning for Biomedical Applications

Requirements for King's College London

Master Program
Requirements
GPA Requirement
Required:3.3
IELTS
Listening
Required:6.5
Reading
Required:6.5
Writing
Required:6.5
Speaking
Required:6.5
Overall
Required:7
TOEFL
Listening
Required:23
Reading
Required:23
Writing
Required:25
Speaking
Required:23
Total
Required:100
Prerequisites
Bachelor's degree in a relevant subject Quantitative competency (for some Economics/Finance programs)
Application Checklist
  • Official Transcripts
  • Personal Statement
  • Two Academic References
  • CV/Resume
  • English Language Proficiency Proof
Specialization Notes

Requirements are consistent across King's Business School and Social Science & Public Policy departments for standard Master's entries.