Numerous studies report an association of certain underlying factors with outcome, for example higher risk factors for contracting a disease. We at Denapsis AI go one crucial step further: we turn data into accurate predictors that are relevant for each individual patient. Through multivariate analyses, we advance the field towards true Precision Medicine, both for diagnosis and treatment choice. While we see improvements in the medical field as most worthy goal, we recognize that there are many other areas that can benefit from our work.

Real-life data is often "noisy", since it is a superposition of a number of  factors. Biomedical measurements, for example, can be distorted by genetic variation, life style, age, gender, the environment,  statistical uncertainty etc. Our methods are optimized for just that: unsupervised AI not  only learns medically relevant patterns, but also how to deal with the  "background" of other factors.

Each  type of data requires its own careful interpretation: we have  experience with genomic and genetic variants, epigenetic modifications  such as DNA methylation or protein binding, RNA expression, protein  biomarkers etc. - and, of course, combinations thereof. Whatever signals  our AI finds, we will link it up to disease, disease susceptibility, or  phenotype.