01.
Clinical Data Structuring (OMOP CDM)
Automating the extraction of clinical information from free-text medical notes with biomedical NLP, standardized into OMOP format for integration into multi-hospital research health data spaces (OHSIRIS).
HEALTH AI SOLUTIONS & CLINICAL COMPUTATION
Artificial Intelligence for Hospitals
Specializing in robust AI solutions for the healthcare industry. Bridging the gap between clinical needs and production-ready software with a strict focus on privacy (GDPR compliance), data integrity, and clinical trust through Explainable AI (XAI).
CLINICAL SPECIALIZATION PILLARS OMOP CDM ONCOLOGY DISCOVERY EEG & APNEA NGS GENOMICS PROTEOMICS & WSI
OMOP CDM NLP extraction & standard health data spaces
Clinical Trials Automated clinical trial candidate matching
Explainable AI Transparent EEG sleep apnea diagnostics
PhD in ML Former EPFL, Basel Hospital, and clinical research lead
Health AI Solutions
Merging scientific rigor with software engineering: AI pipelines designed to operate reliably and ethically in clinical hospital settings.
02.
Oncology Patient Discovery Engine
Search algorithm and clinical web interface identifying candidate patients meeting complex inclusion/exclusion criteria for oncology clinical trials, replacing manual chart reviews with automated investigator alerts.
03.
Explainable AI (XAI) in Medical Signals (EEG)
Machine Learning system to automate sleep phase determination and apnea severity analysis, cutting evaluation time from half a day to minutes. Features visual Explainable AI (XAI) ensuring complete clinical confidence.
04.
Genomic Variant Classification (NGS)
Ion Torrent NGS noise and artifact detection algorithm, delivering high precision and confidence scoring that reduces false positives and accelerates pathologist review times.
05.
Multivariate Analysis of Proteomic Data
Large-scale statistical analysis of proteomic data to identify biomarker profiles and therapeutic targets for precision medicine treatment response (yielding a commercial patent).
06.
Medical Imaging (WSI/Radiology) & Privacy
ML/DL pipelines for pathology Whole Slide Imaging (WSI) and radiology signals. Prioritizes on-premise execution and local LLMs ensuring sensitive patient records never leave hospital infrastructure.
WHO WE ARE
A team built on clinical work and engineering
Engineering and clinical science side by side: every solution starts from a real hospital problem.
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Javier Maroto Morales
PhD in Machine Learning & Software Developer
PhD in AI from EPFL and biomedical software engineer. Leads Iatros' technical architecture and scientific execution.
Frequently Asked Questions
Detailed answers about our health AI engineering, clinical data standards, explainability, and patient privacy.
How do you standardise clinical data with OMOP?
We process free-text clinical notes with biomedical NLP and map them to the OMOP CDM standard, with no manual step.
What does Explainable AI (XAI) mean for a clinical model?
Each prediction shows the specialist which signals drove it, so the final decision always stays with the physician.
How do you protect patient data?
GDPR compliance, pseudonymisation and on-premise deployment: clinical data never leaves the hospital infrastructure.
INITIATE CONTACT
Contact & Collaboration Form
Reach out to discuss your hospital's clinical data integration needs, request a technical demo, or propose a pilot research collaboration.
Direct Email
info@iatros-technologies.com
Response Time
Within 24 business hours
R&D Base
Rector Triado 88, 08014 Barcelona
Confidentiality & Scientific Rigor
All inquiries are handled under strict healthcare data confidentiality and GDPR standards. We do not share inquiries with third parties.