Cancer Genetics.
Quantum lattices for early cancer detection through machine learning.
Abzu reveals early predictive response biomarkers in first-ever clinically viable Myc oncogene inhibitor by Peptomyc®.
Stratifying patients at pretreatment by answering the question: Can we distinguish which patients will respond to OMO-103 treatment at baseline?
Abzu® reveals insights in first-ever clinically viable Myc oncogene inhibitor by Peptomyc®.
Peptomyc used the QLattice and Abzu’s expertise in patient stratification to reveal early predictive response-biomarkers to treatment with OMO-103 in metastatic patients. The analysis by the QLattice was conducted on a very small clinical trial of 22 patients.
Journal of Gastroenterology and Hepatology.
Predicting inpatient mortality in patients with inflammatory bowel disease: A machine learning approach.
Trustworthy data science and good clinical practice.
Good clinical practice requires responsible conduct and considerations of safety and ethics.
Intelligent Health AI
The world’s leading AI-in-medicine summit series. Connecting 200,000 clinicians, technologists, and C-suite executives.
Bioinformatics.
Identifying interactions in omics data for clinical biomarker discovery using symbolic regression.
BMC Medical Informatics and Decision Making.
Combining symbolic regression with the Cox proportional hazards model improves prediction of heart failure deaths.
medRxiv
Symbolic regression analysis of interactions between first trimester maternal serum adipokines in pregnancies which develop pre-eclampsia.
American Journal of Obstetrics & Gynecology.
Explainable “white-box” machine learning is the way forward in preeclampsia screening.
