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DTSTART;TZID=Europe/Stockholm:20240604T110000
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UID:submissions.pasc-conference.org_PASC24_sess162@linklings.com
SUMMARY:MS3H - AI in Life Sciences and Healthcare: Recent Advances, Challe
 nges, and the Path Forward
DESCRIPTION:Minisymposium\n\nAdvances in Artificial Intelligence (AI) are 
 reshaping life sciences and healthcare research. Our minisymposium explore
 s AI's transformative role, delving into Computational Science, Computer V
 ision, and High-Performance Computing (HPC). Sessions span cancer research
 , personalized medicine, interactive machine learning, and privacy-preserv
 ing federated learning offering a panoramic view of AI's applications. In 
 cancer research, Dr. Ellingson discusses the impact of developing models t
 hat integrate biological factors and social determinants of health using H
 PC. Precision imaging, spotlighted by Dr. Gichoya, leverages vast reservoi
 rs of images to advance precision medicine while taking into account the s
 erious ethical concerns. The minisymposium addresses the AI's black box ch
 allenge, crucial for trust and accountability. Dr. Jaeger shares human-cen
 tered approaches for recent developments in probabilistic modeling and exp
 lainable AI in cancer care. Challenges like data availability, scalability
 , and ethical AI practices are focal points. Dr. Madduri discusses federat
 ed learning's potential to build trustworthy AI in life sciences across in
 stitutions. The minisymposium aims to shape ethical standards, foster coll
 aboration, and address the multifaceted challenges of guiding ethical AI i
 ntegration in life sciences and healthcare. We aim to influence best pract
 ices and guidelines, propelling the synergy between AI and life sciences f
 or the benefit of all of us.\n\nImage Based Precision Medicine Using Artif
 icial Intelligence\n\nRecent studies have shown that both biologic and non
 -biologic disease-based characteristics can be predicted from medical imag
 ing. For instance, self-reported race, sex, and age can be predicted from 
 chest X-rays and other imaging modalities, as well as disease conditions, 
 such as ICD code diagnoses...\n\n\nJudy Gichoya (Emory University)\n------
 ---------------\nUnveiling the Tapestry: Exploring the Crucial Role of Soc
 ial Determinants of Health in Cancer Research\n\nThis talk delves into the
  often underestimated yet pivotal role that social determinants of health 
 (SDOH) play in the landscape of cancer research. Beyond the cellular and g
 enetic intricacies, the broader context of an individual's life can signif
 icantly influence cancer outcomes. We will unravel th...\n\n\nSally Elling
 son (University of Kentucky)\n---------------------\nPrivacy-Preserving Fe
 derated Learning-as-a-Service: Building Trustworthy AI Models and Biomedic
 al Insights\n\nFederated learning (FL) is a collaborative learning approac
 h where multiple data owners train a model together under the orchestratio
 n of a central server by sharing the model trained on their local datasets
  instead of sharing the data directly. FL enables creation of more robust 
 models without the ...\n\n\nRavi Madduri (Argonne National Laboratory, Uni
 versity of Chicago)\n---------------------\nAI in Life Sciences and Health
 care: Roundtable Discussion\n\nThis session will be an open discussion of 
 developments, challenges and future directions of AI and life sciences, an
 d how we can guide the way towards ethical, fair and effective integration
 .\n\n\nDestinee Morrow (Lawrence Berkeley National Laboratory)\n\nDomain: 
 Applied Social Sciences and Humanities, Life Sciences, Computational Metho
 ds and Applied Mathematics\n\nSession Chair: Destinee Morrow (Lawrence Ber
 keley National Laboratory)
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