Our data and algorithms enable a more comprehensive longitudinal understanding of cancer, adding clarity to treatment efficacy, patient outcomes, cost, tests/procedures, tumor profiling, and more at a personalized level.
Tools that show treatment plans and the resulting outcomes of sub-populations can drive personalized care for patients, improving patient outcomes and helping providers to manage quality.
Knowledge of what treatments and care deliver the best outcomes for individual patients will ultimately be used to inform decision-making and develop policies that drive value for patients.
Oncology treatment decisions are becoming increasingly complex. With a rise in new innovative therapies and the potential for individualized treatment, the need for strong data-driven evidence and prediction of outcome is increasing. At Precision Health AI we are oncology-focused and driving evidence-based research and analysis to improve care for cancer patients.
Clinical data containing EMR notes, lab results, medical imaging, and genetic sequencing, combined with medical and pharmacy claims provide a granular, temporal representation of a patient. Computational models such as neural networks, bayesian networks, and a variety of supervised and unsupervised ML algorithms provide novel ways to learn patterns and make inferences on that data. This powerful combination of quality data and advanced methods fuels a process of discovery and action on your behalf.