TAIMedImg's Machine learning Accelerator for Structured data Classification (MASC) can process and analyze tabular datasets, automatically generating the best-fitting machine learning model.
MASC explores structured datasets on a regular basis by means of feature selection, machine learning model selection, and parameter tuning, greatly reducing the time burden of model development.
The AI model uses a decision tree algorithm to calculate the patients' Sepsis risk score. This information is then sent back to the hospital, and can act as an additional tool to assist the doctor in making their final diagnosis.
Intelligent Intensive Care Units(ICU) take standard vitals data, and automatically add the appropriate noise and influence parameters into its' prediction algorithm.
Diabetes is a common chronic condition for many citizens, and is known to be linked to multiple kidney diseases, retinopathy, peripheral neuropathy, as well as various other heart conditions.
In order to successfully control the effects of diabetes, early detection and treatment is key. An AI diabetes early detection system uses data regarding the patients' personal medical records, health check records, living habits, as well as ancestry health records to predict whether a current healthy individual is at risk of developing diabetes in the near future.
The earlier the detection, the earlier effective medical treatment can begin.
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