Biomedical and Health Informatics Team (BioHIT)

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About BioHIT

Biomedical and Health Informatics Team (BioHIT) is a meeting team where members and invited speakers give presentations and participate in conversations about biomedical and health informatics, bioinformatics and related fields.

BioHIT meetings begun on April 2016 (initially as BioCAKT meetings) and since then a new presentation take place in Institute of Informatics and Telecommunications, NCSR D, twice a month.

Previous presentations details and relative material are available in this page.

BioHIT seminar presentations

  • Leveraging big data and AI to assess probability of success in drug development

    Presentation outline:
    - Drug development: a burning platform
    - Bringing together disparate data that can lead to better decision making
    - Generating insights with the use of explainable Machine Learning models
    - Applying Machine Learning outcomes to real-world problems: a case study
    - Making the approach practical, and mitigating any risks
    Company description:
    Intelligencia applies predictive analytics on rich and expertly curated data to help pharma/biotech companies better understand and minimize the risk of drug development. Its core product provides estimates of the probability of success (PTRS) of a particular drug, insights on the drivers behind that probability, as well as relevant competitive intelligence.

    Dimitris Skaltsas, Gerry Liaropoulos and Maria Georganaki, 27/2/2019

    Dimitris Skaltsas
    Dimitris has led McKinsey’s team for big data & AI applications in R&D for life sciences, and has built SaaS products focusing on clinical development. He serves as an advisor, and has also invested, in several technology companies with a focus on big data. He is an Executive in Residence for AI at INSEAD.
    MBA (INSEAD), degrees in law (UCL, LMU, University of Athens)

    Gerry Liaropoulos
    Gerry leads the development of our Machine Learning models. Prior to Intelligencia, he spent several years as a quant trader for various asset classes and has built quantitative trading models in commodities, ETFs and futures.
    MSc in Financial Economics from the University of Oxford, Electrical & Computer Engineering from the National Technical University of Athens.

    Maria Georganaki
    Maria is a molecular biologist with a firm background in cancer biology. She has a PhD in immuno-oncology focused on enhancing cancer immunotherapy by modulating the tumor-associated vasculature. In Intelligencia, Maria curates our datasets and contributes to the design of our AI-based products.
    PhD in Medical Science (Uppsala University, Sweden), MSc in Molecular Medicine (Uppsala University, Sweden), Bachelor in Biology (UOA, Greece)

  • Μαθηματικη μοντελοποίηση και προσομοίωση στην ανάπτυξη των φαρμάκων (click for more)

  • Data augmentation as a biologically plausible alternative to explicit regularization in CNNs
    (click for more)

  • Spontaneous transitions of functional connectivity and modular structure in endogenous brain activity (click for more)

  • Machine learning opportunities for a new generation of microwave-based medical devices (click for more)

  • Structured Element Search for Scientific Literature (click for more)

  • Αόρατες Πόλεις. Δομή της χρωματίνης και γονιδιωματική αρχιτεκτονική σε ευκαρυωτικά γονιδιώματα (click for more)

  • HEALTH BANK – A Workbench for Data Science Applications in Healthcare (click for more)

  • Μελέτη αναπαραστάσεων γονιδιωματικών ακολουθιών σε προβλήματα ταξινόμησης (click for more)

  • The In Silico Oncology and In Silico Medicine Group of ICCS-SECE-NTUA and the Large Scale EU-US Research Project CHIC on In Silico Oncology (click for more)

  • Enabling reproducibility in critical care research (click for more)

  • Atom Mapping of Chemical Reactions (click for more)

  • Γενετική του καρκίνου μαστού-ωοθηκών (click for more)

  • RADIO: Unobtrusive, Efficient, Reliable and Modular Solutions for Independent Ageing (click for more)

  • The Thalamic Visual Prosthesis Project (click for more)

  • Όταν το p-value εξορίστηκε ή τι να ΜΗΝ κάνω όταν κάνω έρευνα (click for more)

  • CRISPR/Cas based technology : Taking Gene Editing to the next level (click for more)

  • Drug Repositioning: Existing approaches and applicability for Duchenne Muscular Dystrophy (click for more)

  • Approaches to the atom mapping problem: A review (click for more)

  • Ευρετηρίαση ακολουθιών DNA με τη χρήση χαρακτηριστικών από γράφους Ν-γραμμάτων (click for more)

  • Using Text Mining to Discover Repositioning Opportunities for Orphan Drugs and Rare Diseases (click for more)

  • Machine learning classification of autopsy proven vascular cognitive impairment and Alzheimer's disease using connected speech sampling (click for more)

  • BioASQ: "A challenge on large-scale biomedical semantic indexing and question answering" (click for more)

  • Reaction Map: An efficient atom mapping algorithm for chemical reactions (click for more)

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