Better care begins with better insight.
Pulmonary embolism (PE) is a leading cause of cardiovascular death in the European Union. Despite its severity, PE is a is a mismanaged unmet medical need. It is frequently underdiagnosed, particularly in high-risk patients, resulting into treatment delays and poor clinical outcomes.
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View all →Pulmonary Embolism (PE) is a mismanaged unmet medical need
Leading cause of cardiovascular death in worldwide
Preventable deaths per year in Europe
Mortality if undiagnosed or untreated
Of survivors are readmitted to hospial within 1 year
Direct costs per patient hospitalization
Hospital costs annually in Europe
Turning complex cases into clear paths
Our proof of concept aims to confirm that our solution assists physicians in their decision-making process for managing PE.
iHealthyPath — PE
Is an AI-powered clinical decision support system (CDSS) for PE management; lowering hospital burden and costs, and improving patient care. It aims to address these challenges by exploring how multimodal AI/ML solutions can offer more accurate diagnostic and prognostic insights, reduce clinical workloads and ultimately improve patient outcomes in PE management.
Our Solution Prototype Features
Pulmonary Embolism Response Teams Dashboard
Unified interface to manage patients with Pulmonary Embolism across physicians especialties and care settings.
Early Detection of Pulmonary Embolism
identifies potential pulmonary embolisms at their earliest signs, triggering timely alerts so physicians can act before the condition becomes critical to enable early intervention and preventing life-threatening complications.
Prognosis
Forecasting patient outcomes through AI-driven insights that help physicians anticipate complications and guide treatment decisions.
Risk Analytics
Quantify and understand each patient’s risk by analyzing key factors, such as smoking history or recent surgery, to support personalized care.
Evidence Based Insights
Deliver clear, evidence-backed guidance that explains the “why” and “what now” behind every AI output to turn predictions into actionable clinical decisions.
Continuous Learning
Leverages real-world feedback from clinical practice to continuously refine its algorithms, ensuring ever-improving performance, adaptability, and trust in evolving hospital environments.
Leadership and advisors
Abel Díaz Berenguer
CTO
Senior AI/ML Researcher Engineer at ETRO‑VUB
Visionary – Impact‑Driven – Agile
Hichem Sahli
CEO | CSO
Prof at ETRO‑VUB | Principal scientist at IMEC
Strategic Leadership
Interdisciplinary – Innovator – Visionary – Impactful
Arne Pauwels
Business Growth Advisor
Spin‑off coach & management at VUB
Nikos Deligiannis
Principal Scientific
Professor at ETRO‑VUB | Senior SP/AI/ML scientist at IMEC | ERC Grantee
Koenraad Nieboer
Medical Expert
Professor at VUB | Senior Staff Member, Emergency Radiology at UzB
Enrique Vega
Business Development Advisor
CEO & Co‑Founder at Azalea Vision
Become a pilot site
Work with us to co‑design workflows, validate outcomes, and scale safely.