Dive Into the New Age of Accelerated Analytics
Processes
Data Acquisition
Acquiring diverse datasets and imaging modalities related to various diseases, ensuring a comprehensive dataset that captures the nuances of each condition.
Preprocessing
Employing advanced preprocessing techniques to clean and enhance the quality of the collected data. Extracting relevant features from the dataset provide machine learning models with meaningful input.
Model development and training
Building handcrafted ML models, training them on the preprocessed dataset to recognize patterns and correlations associated with different diseases and continuously refining and optimizing these models.
Validation and Deployment
Validating models on distinct datasets to ensure generalization, then deploying for real-world applications, empowering healthcare professionals with AI for diagnosing diseases and achieving better outcomes.
