Opportunities and challenges in data sciences with diverse imaging technology
Abstract Number:
1144
Submission Type:
Invited Paper Session
Participants:
Jian Kang (1), Hongtu Zhu (2), Jian Kang (1), Yang Chen (1), Simon Vandekar (3), Daiwei Zhang (4), Laurent Younes (5)
Institutions:
(1) University of Michigan, Ann Arbor, (2) University of North Carolina, Chapel Hill, (3) Vanderbilt University, Nashville, (4) University of Pennsylvania, Philadelphia, (5) Johns Hopkins University, Baltimore
Chair:
Discussant:
Session Organizer:
Speaker(s):
Session Description:
As we navigate an increasingly data-centric world, the fusion of Data Sciences with diverse imaging technologies is opening novel corridors for research and application. This interdisciplinary session brings together an exceptional panel of experts to spotlight this fusion.
Our first presentation (Dr. Daiwei Zhang) introduces iStar, a groundbreaking method that combines spatial transcriptomics and high-resolution histology. This technique paves the way for Data Sciences to revolutionize gene expression mapping at unprecedented scales.
Our second speaker (Dr. Laurent Younes) continues to focus on spatial transcriptomics, tackling the complex issue of atlas to data alignment. By employing advanced algorithms like large deformation diffeomorphic mapping, the talk will explain how Data Sciences can solve non-linear spatial transformations for more accurate cell-type probability distributions.
The third presentation (Dr. Simon Vandekar) explores the neuroscience domain through the lens of Brain-wide Association Studies (BWAS). With an emphasis on data analytics, the talk will highlight how Data Sciences can offer nuanced approaches to improve replicability and power in BWAS.
Our fourth talk (Dr. Yang Chen) centers on space weather forecasting and introduces VISTA, a Data Science-based method for the accurate imputation and prediction of Total Electron Content (TEC) maps essential for GPS operations globally.
Highlight on Diversity:
Our panel is notably diverse, featuring female speakers and a range of career stages-from senior and mid-career faculty to postdoc researchers. This breadth adds multiple perspectives to the conversation, enriching our exploration of Data Sciences and diverse imaging technologies.
Special Discussant:
We are privileged to feature a world-leading expert (Dr. Hongtu Zhu) in imaging statistics and machine learning as our discussant. Their role will be pivotal in synthesizing the technical facets and diverse views presented, offering a holistic understanding of the current landscape of Data Sciences in imaging technology.
Through this rich and multifaceted session, attendees will not only gain a deeper understanding of the role Data Sciences play in diverse imaging disciplines but also engage in meaningful dialogue that could lead to future interdisciplinary collaborations.
Sponsors:
Biometrics Section 2
International Chinese Statistical Association 3
Section on Statistics in Imaging 1
Theme:
Statistics and Data Science: Informing Policy and Countering Misinformation
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Applied
Yes
Estimated Audience Size
Medium (80-150)
I have read and understand that JSM participants must abide by the Participant Guidelines.
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I understand and have communicated to my proposed speakers that JSM participants must register and pay the appropriate registration fee by June 1, 2024. The registration fee is nonrefundable.
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