The Affiliated Hospital of China Medical University (China Affiliated Medicine) cooperated with Microsoft to develop the “AST.AI Smart Antimicrobial Antimicrobial Prediction System” on the Azure platform. With the help of AI machine learning analysis, it will take 2-5 days to know “Bacteria resistance” results, shortened to 1 hour.
This achievement has been recognized by international medical journals and has attracted the cooperation of domestic and foreign clinical research units. In the future, the model results and analysis data will be shared with global medical institutions through the Azure platform to jointly create a more complete smart antibacterial system. to solve the world‘s biggest healthcare challenges.
You Jiaxin, director of the Smart Science and Technology Innovation Center of China Affiliated Medicine (referred to as the Innovation Center), pointed out that the “AST.AI Smart Antimicrobial Antimicrobial Prediction System” uses mass spectrometry to interpret protein quality for drug resistance prediction, and increases the model through molecular chimera of bacteria and antibiotics. Biological significance, using the Microsoft Azure Machine Learning platform and collaborative environment, with limited human and material resources, to rapidly develop machine learning algorithms, and use a large amount of clinical data to train the accuracy of the model.
At present, the model or data has been shared with 4 hospitals in China. We are looking forward to AST.AI’s further cooperation with Microsoft, sharing with Europe and the world, and feeding data from various countries for verification, so that drug resistance prediction can be more accurate and in line with local conditions. need.
Microsoft Taiwan pointed out that the development of the “AST.AI Smart Antibiotic Antibiotic Prediction System” is mainly based on the two major challenges faced by the medical community against the abuse of antibiotics. A heavy burden on medical centers around the world.
You Jiaxin pointed out that in the past, patients with infection had to go through processes such as blood culture and drug resistance comparison before antibiotics were administered.
However, statistics show that for every 1 hour delay in medication, the mortality rate of patients will increase by 7.6%. The team of China Affiliated Medical Innovation Center developed a cloud-native AST.AI system through the Azure platform, connecting the mass spectrometer signal and machine learning algorithm, and applying it to the prediction of bacterial resistance mechanism, and highly integrated with the workflow of the testing laboratory. Anti-drug results can be obtained in just 1 hour, which assists in precise clinical administration of drugs, which not only reduces costs, but also saves the health of patients in time.
(Source of the first image: Microsoft Taiwan)
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