ExpertiseUpdated on 4 November 2025
GenAI-Powered Personalised Medicine: Multimodal Digital Biomarkers & Clinician-in-the-Loop Therapy Suggestion
Head of International Projects at ViFrameAI
İstanbul, Türkiye
About
ViFrameAI develops Deep Learning (DL) and Generative AI (GenAI) for personalised medicine. Our stack fuses medical imaging, -omics, pathology and EHR to build digital biomarkers and clinician-in-the-loop therapy-suggestion support that is deployable on-prem/edge or cloud with strong privacy safeguards.
Core capabilities
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Multimodal biomarker discovery: fusion transformers and temporal models for prognosis, response and toxicity prediction.
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GenAI therapy-suggestion support: evidence-retrieval and ranking of guideline-concordant options and trial matches; outputs rationale, uncertainty and citations (decision support, not autonomous).
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Trustworthy AI: calibration targets (e.g., ECE), explainability (feature attributions, counterfactuals), subgroup bias audits, model cards/datasheets.
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Privacy & deployment: federated learning, differential privacy, consent & minimization; integration via REST/gRPC; hospital-ready edge deployments.
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Synthetic data & rare cohorts: GenAI augmentation pipelines to improve coverage while protecting privacy.
Domains & pilots
Oncology (CRC, derm), gastroenterology/endoscopy, computational pathology, patient safety/triage.
Contact
selay.yuksel@viframeai.com
Organisation
Similar opportunities
Expertise
- Tools for secure data sharing & secondary use (pseudonymisation, FAIR data)
- Data integration & interoperability solutions (EHRs, registries, data platforms)
- Implementation of CE-marked digital health solutions (AI algorithms, software, apps)
Selay Yüksel
Head of International Projects at ViFrameAI
İstanbul, Türkiye
Expertise
Citogenetics and Functional Genomics
- Receiver institution with a need to adopt a PM approach
- Clinical decision support systems for personalised medicine
- Personalised treatment pathways (tailored therapies, precision dosing)
- Patient management systems (decision-support tools, clinical workflows)
- Screening & early detection programs (risk stratification, predictive tools)
- Adaptation of care pathways for PM (embedding new tests/therapies into routine care)
Inês Costa
Research Manager at Universidade de Coimbra - Faculdade de Coimbra
Coimbra, Portugal
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
Coimbra, Portugal