Scaling AI solutions in healthcare, steps towards proactive care
Healthcare systems around the globe are facing value challenges. The most recent one was the virus pandemic and the sudden need for new healthcare services. The second one is an escalating demand from long-term, non-communicable diseases and the aging population where increased commitments are limited by scarce resources. Managing these challenges is expensive and to improve the situation, the healthcare system is suggested to transform from an episodic hospital-centric care-based approach to become more proactive, and democratized. Information driven care has the potential to address some of these challenges due to the increasing availability of high quality big data within the healthcare domain; yet there are several challenges in order to scale the AI solutions. The scaling of AI deployment would be fueled by a combination of AI advancements, enculturation, and empowerment within organizations. In this talk, I will focus on a few of such challenges and how the state-of-the-art research within AI can be utilized to mitigate them.
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Farzaneh
Scaling AI solutions in healthcare, steps towards proactive care
Healthcare systems around the globe are facing value challenges. The most recent one was the virus pandemic and the sudden need for new healthcare services. The second one is an escalating demand from long-term, non-communicable diseases and the aging population where increased commitments are limited by scarce resources. Managing these challenges is expensive and to improve the situation, the healthcare system is suggested to transform from an episodic hospital-centric care-based approach to become more proactive, and democratized. Information driven care has the potential to address some of these challenges due to the increasing availability of high quality big data within the healthcare domain; yet there are several challenges in order to scale the AI solutions. The scaling of AI deployment would be fueled by a combination of AI advancements, enculturation, and empowerment within organizations. In this talk, I will focus on a few of such challenges and how the state-of-the-art research within AI can be utilized to mitigate them.
Biography:
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.