We are the first company to establish a quantitative biochemistry platform for the analysis of gene gene co-expressions. Our self-developed deep learning service model provides a comprehensive and structural strategy to determine the gene gene co-expressions network of cancers and other diseases related to Nucleophosmin (NPM1/B23). This model provides important data for health assessment, disease diagnosis, prognosis and treatment, and for related drug development.
Our focus has been on cancer-related research and we have successfully obtained important quantitative medical data such as ovarian cancer, breast cancer, pancreatic cancer, liver cancer (viral infection), colorectal cancer, lung cancer, and other related cancer recurrence prediction, cancer stage assessment, chemoresistance, metastasis, and distinguishing low-risk and high-risk patients, etc.
Our Artificial Intelligence deep learning service model has sufficient scalability and can be extended to other diseases, such as viral infectious diseases (such as SARS-related coronavirus and HIV), and degenerative diseases (such as cardiovascular disease, Osteoarthritis, Alzheimer, etc.), and metabolic diseases (such as diabetes, etc.). This model quantifies the interaction between genotypes and phenotypes so that the interaction between genes can be seen, diseases’ pathogenesis and causes can be known, risks assessment can be made, drug responses and resistance can be known for treatment strategy and recommendations (both Chinese and Western medicine).
Promote biomedical research and healthcare through Deep Learning and Artificial Intelligence
Continue to look for important evidence about disease and make it available for medical and health care providers to treat patients with the most suitable therapeutic solutions
