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Advancing Precision Medicine:
Multi-Modal Analysis and Imaging for Enhanced Diagnosis and Treatment.
The field of precision medicine has witnessed remarkable advancements in recent years, with multi-modal analysis and imaging emerging as essential tools for improving diagnosis, treatment, and patient outcomes. This webinar aims to explore the growing significance of imaging in precision medicine applications and discuss the transition towards integrating machine learning and artificial intelligence (ML-AI) techniques in multi-modal analysis in the cloud.
What will you learn in this webinar?
- How multi-modal analysis and imaging can enhance diagnosis and treatment in precision medicine
- Strategies for integrating ML-AI techniques into scalable multi-modal analysis
- The challenges and ethical considerations associated with multi-modal analysis and imaging in precision medicine
- Interoperability strategies to seamlessly integrate data from multiple domain-specific repositories to empower multi-modal analysis in the cloud
- Resources and tools available for researchers and healthcare professionals interested in multi-modal analysis and imaging.
- The latest advancements and role of machine learning and artificial intelligence (ML-AI) in multi-modal analysis
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Meet the speaker.
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Surya Saha, PhD
Dr. Saha is a Technical Program Manager in the Scientific Programs team at Velsera. He has a background in computer science, databases, omics analysis and biological data management and integration. He has worked with cross-matrixed teams of geneticists, molecular biologists, engineers, product development managers and software developers on a range of genomics, metabolomics, proteomics, metagenomics, microbiome and transcriptomics projects across academia and industry.
His role at Velsera is to develop data integration and interoperability strategies to empower computational and experimental research based on scalable and cloud-agnostic analysis of large biomedical datasets. Prior to joining Seven Bridges, now known as Velsera, he led the bioinformatics efforts in several large agricultural consortia handling multi-modal data types.
He leads the NIH-funded Cancer Data Aggregator program at Velsera, integrating multi-omics data from Cancer Research Data Commons for users on the Cancer Genomics Cloud platform. He co-manages various programs on the NIH-funded CAVATICA platform, including the Gabriella Miller Kids First program for childhood cancer and birth defects, the INCLUDE project for Down syndrome, and the NIH Common Fund Data Ecosystem collaborative program. He actively participates in GA4GH and NIH Cloud Platform Interoperability meetings, guiding the development of open standards and specifications.
Dr. Saha trained as a postdoctoral researcher at Cornell University following which he led a number of plant, plant pathology and arthropod multi-omics projects as a Senior Research Associate at the Boyce Thompson Institute. He earned his Ph.D. in computer science from Mississippi State University.
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