h2health/science applies machine learning and rigorous statistics to clinical data, helping clinicians and researchers see more in oncology images and blood analyses.
Deep learning models that analyse histopathology and radiology images to detect, segment and characterise tumour tissue, supporting faster, more consistent assessment by clinicians.
Statistical and machine-learning methods that uncover how blood parameters depend on one another and on clinical factors, turning routine lab values into interpretable, actionable insight.
Careful preparation, annotation and quality control of clinical images and laboratory data, with privacy built in.
Methods chosen for both accuracy and explainability, so every result can be traced and understood.
Close collaboration with clinicians to test results against real-world practice before they inform care.
Clinics, research groups and industry partners: we’d be glad to hear about your data and the questions you want to answer.