Healthcare is poised to take advantage of Machine Learning to help diagnose issues faster and more accurately. By providing a large sample set, along with a diagnosis - either positive or negative, Machine Learning can achieve results that beat the average doctor's assessment. In addition, the tool can be used to help new doctors make correct decisions and also assist in areas where there is poor medical aid.
A good example of this is - determining if there is retinal damage. The following was discussed at the TensorFlow 2017 Summit sponsored by Google.
Diabetic retinopathy is the fastest growing cause of blindness. Learn from Lily Peng how TensorFlow was trained to analyze retinal fundus images to diagnose this condition. See the video at:
A good example of this is - determining if there is retinal damage. The following was discussed at the TensorFlow 2017 Summit sponsored by Google.
Diabetic retinopathy is the fastest growing cause of blindness. Learn from Lily Peng how TensorFlow was trained to analyze retinal fundus images to diagnose this condition. See the video at:
