Transitioning from Data to Patient Benefit: A Use-Case Passed
Monday May 22, 2023 10:00 - 14:00 G1
Lecturers: Amira Soliman, Atiye Sadat Hashemi, Jens Lundström, Kobra Etminani, Louise Wandel, Sadi Alawadi
Track: MIE: Decision support
Separate registration required: https://www.mie2023.org/tutorials
Transitioning from data to a clinical decision support system able to benefit patients involves a plethora of perspectives within the following domains: clinical, legal, technical, managerial, and system development.
This requires multiple partners such as healthcare providers, universities, authorities and technology providers to join forces. In this tutorial the partners Region Halland, Sahlgrenska University Hospital, Swedish Authority for Privacy Protection, Halmstad University, AI Sweden, HallandiaV, and the Netherlands eScience Center will give their perspectives and deep-dive into several of the challenges and possibilities of the realization of Clinical Decisions Support Systems (CDSS), for the specific use-case of heart failure readmission prediction.
Language
English
Seminar type
On site only
Level of knowledge
Advanced
Conference
MIE
Authors
Jens Lundström, Atiye Sadat Hashemi, Amira Soliman, Kobra Etminani, Sadi Alawadi, Louise Wandel
Lecturers
Amira Soliman Lecturer
Assistant Professor
Högskolan i Halmstad
My research experience spans distributed systems, data analysis, and machine learning with a focus on interlinked data analysis using graph theory for complex and large systems. My research is directed towards the exploration of new algorithms for supporting the design and implementation of robust and large-scale learning algorithms, especially in healthcare. I believe artificial intelligence and machine learning can offer more personalized and scalable solutions for better information-driven healthcare.
Jens Lundström Lecturer
Senior Lecturer in Machine Learning
Högskolan i Halmstad
I'm a lecturer and researcher at Halmstad University, Sweden. My duties include research, leadership and teaching in the domain of Machine Learning and AI. Specifically, I'm interested in applied and theoretical ML research for improving healthcare, patient experience and quality of life.
Kobra Etminani Lecturer
Associate Professor, Docent
Center for Applied Intelligent Systems Research (CAISR) in Health, Halmstad University
Kobra (Farzaneh) Etminani is an associate Professor, Docent, working at the Center for Applied Intelligent Systems Research (CAISR), Halmstad University, Sweden. She is Deputy Profile Manager for CAISR Health, a Swedish funded research profile. She is also part of the extended management group for Information Driven Care research program (IDC) at Halmstad University.
She manages the Real-World Evidence (RWE) research projects together with Health Data Center (HDC), that includes several research projects together with Region Halland (a regional Swedish healthcare system), analytics companies, and big Pharma.
She has worked on various topics and application areas within Machine Learning (ML), Artificial Intelligence (AI), Data Mining, and Deep Learning (DL) in the last decade, focused on healthcare, district heating, and mobility. Her main research interest is focused on solving real-world problems, which is focused on a healthier society, with the help of AI and ML, if possible and applicable. Her recent research focus is on patient trajectories and eXplainable AI (XAI) in precision healthcare
Louise Wandel Lecturer
Halmstad University
Sadi Alawadi Lecturer
Halmstad University