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AI has been widely used to diagnose diseases in clinical situations and assist medical professionals in determining the best course of therapy. However, one of the most significant difficulties that healthcare organisations face is data collection. For providing the best possible healthcare solutions to patients, it is very important that medical data be easily shared across organisations.
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Use Cases
Due to data privacy concerns, it is very difficult for healthcare organisations to share patients’ data. If such data could be shared across different departments and organisations while preserving patient privacy, many applications can be unlocked. With betterdata, patients' data can be easily shared within internal teams as well as external organisations.
In medical institutes that are highly regulated, data often exists in isolated silos and is insufficient to train an AI model that can offer good accuracy. betterdata offers robust data augmentation techniques to address situations where there is a lack of data, by synthesising data without changing its inherent structure.
ML models are being frequently used for diagnosis of different diseases in the clinical domain. If subject selection is done incorrectly, the dataset can end up being heavily imbalanced and skewed. With betterdata, your datasets can be balanced to ensure that your AI models are not trained on the wrong data.
