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ExpertiseUpdated on 14 October 2025

Health Informatics

Health Informatician at Health Data & Policy Lab

Istanbul, Türkiye

About

We focus on leveraging large-scale hospital datasets to advance data-driven healthcare and precision medicine. Our expertise combines bioinformatics, computational biology, and predictive modelling to transform genomic and clinical data into actionable insights. With access to extensive datasets from major hospitals, we offer opportunities for partners interested in developing novel analytical approaches, validating predictive tools, and exploring applications of health data in clinical practice. Alongside this data-driven capacity, our team also brings a complementary perspective from qualitative research and science and technology studies, contributing reflections on trust, reliability, and the social dimensions of data use. This dual strength enables us to build collaborations that are both technically rigorous and contextually informed. We are open to engaging with academic, clinical, and industry partners seeking to co-develop innovative approaches to health data science, and to ensure that these approaches are sustainable, impactful, and aligned with broader healthcare challenges.

Field

  • Screening & early detection programs (risk stratification, predictive tools)
  • Clinical decision support systems for personalised medicine
  • Standardisation & evaluation methodologies (protocols, metrics, QA/QC processes)
  • Cultural/organisational change approaches (staff training, workflow redesign)

Organisation

Health Data & Policy Lab

Research organisation

Istanbul - Ankara, Türkiye

Similar opportunities

  • Expertise

    Advancing Personalized Medicine Through Integrative Research and Clinical Excellence

    • Receiver institution with a need to adopt a PM approach
    • Clinical decision support systems for personalised medicine
    • Theranostics (combined diagnostic + therapeutic approaches)
    • Diagnostic tools (biomarkers, genetic tests, companion diagnostics)
    • Personalised treatment pathways (tailored therapies, precision dosing)
    • Patient management systems (decision-support tools, clinical workflows)
    • Partial adoption of a PM solution (testing selected modules/components)
    • Tools for secure data sharing & secondary use (pseudonymisation, FAIR data)
    • Screening & early detection programs (risk stratification, predictive tools)
    • Recovery & follow-up support systems (digital monitoring, apps, telemedicine)
    • Cultural/organisational change approaches (staff training, workflow redesign)
    • Data integration & interoperability solutions (EHRs, registries, data platforms)
    • Standardisation & evaluation methodologies (protocols, metrics, QA/QC processes)
    • Adaptation of care pathways for PM (embedding new tests/therapies into routine care)
    • Patient engagement & empowerment strategies (self-management tools, shared decision-making)
    • Adaptation of an existing PM solution to local context (language, IT environment, regulations)
    • Initiating implementation of a PM solution (pilot site setup, proof-of-concept in clinical practice)

    Inês Costa

    Research Manager at Universidade de Coimbra - Faculdade de Coimbra

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  • Expertise

    Doctor of Medicine, Cardiology specialist

    • Clinical decision support systems for personalised medicine
    • Theranostics (combined diagnostic + therapeutic approaches)
    • Full adoption/acquisition of a PM solution into clinical practice
    • Patient management systems (decision-support tools, clinical workflows)
    • Recovery & follow-up support systems (digital monitoring, apps, telemedicine)
    • Standardisation & evaluation methodologies (protocols, metrics, QA/QC processes)
    • Implementation of CE-marked digital health solutions (AI algorithms, software, apps)
    • Adaptation of care pathways for PM (embedding new tests/therapies into routine care)

    Filonid Aliu

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    Liverpool, United Kingdom

  • Expertise

    Machine Learning

    • Clinical decision support systems for personalised medicine
    • Diagnostic tools (biomarkers, genetic tests, companion diagnostics)
    • Personalised treatment pathways (tailored therapies, precision dosing)
    • Patient management systems (decision-support tools, clinical workflows)
    • Screening & early detection programs (risk stratification, predictive tools)
    • Recovery & follow-up support systems (digital monitoring, apps, telemedicine)

    Tugba Onal-Suzek

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