Your own data
Cost: Free during Beta
This model assists the radiologist to segment lesion and do positive/negative classifications based on lung CT.
Chest CT Dicom series of 1mm or 5mm.
The diversity of the training data is limited. The evaluation of the model is not on a comprehensive dataset.
The model uses deep neural networks, trained on data from several sources in China in an end-to-end manner.
Accuracy: 0.9 (negative/positive)
The model structure is the same as before, however, more training data labelled by experienced radiologist/with PCR results are added in.
This high-tech company specializes in artificial intelligence in medicine.