[PDF] a guide to deep learning in healthcare

  • How is deep learning used in healthcare?

    The deep learning and machine learning g are able to find the normal and abnormal data of the patients, by that the doctors can detect the condition of patients. Machine learning is also known as artificial intelligence, which is used for recognizing or diagnosing the real-time condition of the patients.

  • What are the challenges of deep learning in healthcare?

    5 Challenges of Using Deep Learning in Healthcare

    5.1 The Volume of Healthcare Data. Deep learning represents a set of computational models that are extremely expensive [44]. 5.2 Quality of Healthcare Data. 5.3 Handling Healthcare Data Stream. 5.4 Temporality. 5.5 Complexity in Domain. 5.6 Interpretability.

  • How to learn deep learning step by step?

    14 Steps for Learning Deep Learning. A handy list of resources to help you become a deep learning expert. 2Step 0: Learn Machine Learning Basics. (Optional but recommended) 3Step 1: Dig into Deep Learning. 4Step 10: Pick a focus area and go deeper. 5Step 11: Build Something.
  • Now moving onto applications to detect health conditions, deep learning techniques used in EHR can allow physicians to analyze information and detect heart problems, determine the amount of glucose in a diabetic patient, interpret MRI's and CT scans with minor human supervision, to search for cancer cells and diagnose
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