1. A computer-implemented method for predicting answers to questions concerning medical image analytics reports, the method comprising: splitting a medical image analytics report into a plurality of sentences; generating a plurality of sentence embedding vectors by applying a natural language processing framework to the plurality of sentences; receiving a question related to subject matter included in the medical image analytics report; generating a question embedding vector by applying the natural language processing framework to the question; identifying a subset of the sentence embedding vectors most similar to the question embedding vector by applying a similarity matching process to the sentence embedding vectors and the question embedding vector; and using a trained recurrent neural network (RNN) to determine a predicted answer to the question based on the subset of the sentence embedding vectors.
2. The method of claim 1 , wherein each respective sentence embedding vector is generated by: generating an embedding for each word in a particular sentence using the natural language processing framework; and averaging the embedding of each word in the particular sentence to yield the respective sentence embedding vector.