PyCon APAC 2023

Hassan Sami Adnan

Sami is a healthcare professional and digital health designer currently reading for a doctoral degree, DPhil in Primary Health Care, at the University of Oxford. His research looks at the characteristics and mechanisms of using human centred AI design to address multiple long-term conditions (multimorbidities) at the intersection of the digital transformation in healthcare.
Previously, he worked as a Research Fellow at the Berlin Institute of Health at Charité University Hospital Berlin with the Core Interoperability Unit. Prior to that he worked as a Healthcare Researcher with the WHO and the Medical Faculty of Maastricht University, on a project related to SDG 3 – resulting in the WHO Community Engagement Health Promotion Guide.
With his background in healthcare and digital health, his areas of research interests are in medical AI Ethics, explainable AI, health design innovation, patient data privacy, digital health regulation, and the application of artificial intelligence in healthcare systems.
Sami has researched on 3D printing for personalised medicine and has recently developed the Healthcare Differential Privacy Framework to make privacy-preserving data sharing viable for medical research and machine learning. Sami has also worked at Apple Inc. for 8 years in different roles ranging from sales and product development to training new employees and designing company-internal solutions.


Session

10-27
13:40
30min
Python in Human-Centered AI Design: How to deal with 60 Million patients to develop AI solutions in healthcare
Hassan Sami Adnan, Samara Sharmeen

We introduce a novel design approach to design, develop, deploy, and maintain AI/ML tools. This real-world research case study in the healthcare domain, to solve societal issues, can provide actionable methodology for any DevOps task using Python. The presented design methods demonstrate how Python is used in all stages of research with data collected from 60 million patients in United Kingdom.

Approaching to social problem
track 3