分分飞艇下载网站_Medical tech firm to promote AI diagnostic system in hospitals
Sh分分飞艇下载网站anghai Ev分分飞艇下载网站omics Medical Technology Co, a company specialized in developing sol分分飞艇下载网站utions fo分分飞艇下载网站r tumor characterization and prognostic prediction, plans to push its individually disease-specific clinical diagnostic supporting system into more Chinese hospitals over the next decade.
Based on the clinical data for multimodal medical imaging data including MRI, CT, PET/CT and PET/MRI scanners, as well as multidisciplinary medical omics resources such as genomics, proteomics and metabolomics, the company has built a multimodal molecular imaging artificial intelligence platform to cut the probability of misdiagnosis.
"In clinical practice, the conventional medical imaging examinations have limited sensitivity and specificity in early tumor diagnosis, and tissue biopsy normally can be affected by tumor heterogeneity or the interobserver or intraobserver variability, so that those tumors often hidden in the body failed to be found and were misdiagnosed," said Wang Shiwei, the company's chief executive officer.
By quantitatively collecting all 分分飞艇下载网站kinds of imaging data from patients with different types of tumors, conducting quantitative radiomics analysis, and combining other multigroup data, Wang said the results are presented to doctors in the form of 3D rendering visualizations, so the doctors can fully understand the patient's genotype and tumor phenotype, activity, molecular biomarkers and microenvironment, and finally achieve a more accurate, effective oncology treatment.
Supported by its research team in Austria, the company has been partnering with a number of large-scale hospitals in Beijing, Shanghai and Chengdu to conduct research and development of more than 25 cancer disease prediction models, including prostate cancer, gliomas, lung cancer, pancreatic cancer, lymphoma, cervical cancer, breast cancer and esophageal cancer.
"For large, well-equipped hospitals, our products can be installed in hospitals' workstations, so that doctors can use models gained from our solution to predict the molecular information of the tumor," said Li Xiang, chief scientific officer at Evomics. "For smaller hospitals, the data can be desensitized after transmission to the cloud for data analysis before sending back the results to the hospital."
Marcus Hacker, a professor and head of the nuclear medicine division at Medical University of Vienna, said with AI technology, this platform is able to provide a comprehensive auxiliary diagnosis scheme for tumor classification stage, prognosis survival period, recurrence risk, drug response rate and other oncology diagnosis and treatment process.