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DTSTART;TZID=Europe/Stockholm:20240604T160000
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UID:submissions.pasc-conference.org_PASC24_sess122@linklings.com
SUMMARY:MS4H - Synergizing AI and HPC for Pandemic Preparedness with Genom
 ics and Clinical Risk Assessment
DESCRIPTION:Minisymposium\n\nTo address emerging virus variants, our strat
 egy integrates next-gen vaccines and personalized disease treatments. In B
 ioinformatics Sequencing, HPC and AI power vaccine development and infecti
 on control. Simultaneously, AI-Driven Clinical Risk Assessment aids health
 care in pandemics. Personalized disease stratification involves AI models 
 for risk assessment and interpretability-guided deep learning in medical a
 pplications. Standardizing EHR and Federated Learning ensures data integri
 ty and privacy. In Bioinformatics Sequencing, we tackle challenges through
 : Drug Discovery for Next-Gen Vaccines: Applying bioinformatics to identif
 y therapeutic candidates from genomic data for infectious diseases. Evolut
 ionary Analysis for Infection Spread: Analyzing viral sequence data to ide
 ntify important genes, functions, and evolution for minimizing and trackin
 g infection spread. Accelerating Genotype-Phenotype Workflow: Correlating 
 genotype to phenotype for efficient drug discovery in functional genomics.
  For AI-Driven Clinical Risk Assessment, methods include: AI Models for Di
 sease Progression: Using advanced deep learning to characterize disease su
 btypes based on unsupervised and supervised learning. Interpretability-Gui
 ded Deep Learning: Enhancing comprehension in medical AI by addressing bia
 s, shortcut learning, and susceptibility to attacks. Standardizing EHR and
  Federated Learning: Ensuring uniform Electronic Health Records (EHRs) usa
 ge, standardizing data formats, and addressing privacy concerns through fe
 derated learning. This minisymposium brings together experts to accelerate
  pandemic preparedness with clinico-genomic-data to improve diagnosis.\n\n
 Enhancing Bioinformatics Research Efficiency in Supercomputer Environments
  with Artificial Intelligence Support\n\nEfficient analysis of Big Data pr
 esents unique challenges across molecular biology, genetics, biomedical sc
 iences, and healthcare, particularly in advancing personalized diagnostics
  and therapeutics. This necessitates innovative strategies for effective i
 nformation management. Here, we explore the e...\n\n\nKary Ann del Carmen 
 Ocaña Gautherot (LNCC); Douglas Cardoso (Polytechnic Institute of Tomar); 
 and Micaella Coelho, Alexandre Porto, and Carla Osthoff (LNCC)\n----------
 -----------\nThe German Human Genome-Phenome Archive: Advancing Towards a 
 Federated Infrastructure for Managing and Analyzing Genomics and Phenotypi
 c Data\n\nThe German Human Genome-Phenome Archive (GHGA) is dedicated to a
 ddressing the challenges of managing human genomics and phenotypic data. A
 s part of the German National Research Data Infrastructure (NFDI), it conn
 ects German researchers to the global genome research landscape, in collab
 oration with i...\n\n\nLuiz Gadelha (GHGA)\n---------------------\nMutatio
 n Count Alone does not Predict the Severity of Common Variants of SARS-CoV
 -2\n\nSARS-CoV-2 Omicron variants BA.2.86 and JN.1 have mutations that hav
 e raised concerns over their health impact. Genomic surveillance of JN.1 h
 as shown it to be the dominant variant circulating in the USA.\n\nEmpirica
 l studies on immune evasion and transmissibility on BA.2.86 and JN.1 are c
 ontradictory...\n\n\nDaniel Janies, Shirish Yasa, Sayal Guirales-Medrano, 
 Denis Jacob Machado, and Colby Ford (University of North Carolina, CIPHER 
 Center)\n---------------------\nEnhancing Pandemic Preparedness: AI Models
  for Risk Assessment and Disease Progression\n\nThis talk outlines the dev
 elopment of AI models for Risk Assessment and Disease Progression in Pande
 mic Preparedness. Leveraging advanced deep learning techniques, these mode
 ls integrate diverse data sources like images, clinical features, and labo
 ratory data to characterize disease subtypes and per...\n\n\nAlexander Poe
 llinger (University of Bern)\n\nDomain: Chemistry and Materials, Engineeri
 ng, Life Sciences, Computational Methods and Applied Mathematics\n\nSessio
 n Chairs: John Anderson Garcia Henao (University of Bern, ARTORG Center fo
 r Biomedical Engineering Research) and Kary Ann del Carmen Ocaña Gautherot
  (LNCC)
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