HIPAA protection for medical images

1 . A computer implemented method comprising:

receiving, from a provider server and at an image processing server, medical data including at least one image;

determining, by the image processing server using a neural network, the at least one image within the medical data contains PII;

in response to determining that the at least one image in the medical data contains PII, classifying, by the neural network, at least one medical characteristic of the image;

generating, by the image processing server using the medical characteristic classification, at least one metadata tag that describes the medical characteristic;

modifying, by the image processing server, the medical data to replace the image with the generated metadata tag; and

transmitting, by the image processing server to a transaction server, the modified medical data.

2 . The method of claim 1 , further comprising:

receiving, by the image processing server, correction data that indicates a classification, different from the classification determined by the neural network, to be used to generate the at least one metadata tag; and

modifying, by the image processing server, the at least one metadata tag based on the correction data.

3 . The method of claim 2 , further comprising:

retraining the neural network on the received correction data.

4 . The method of claim 1 , wherein the neural network is trained on previous classifications made in other instances of medical data.

5 . The method of claim 1 , wherein the medical characteristic is a medical condition.

6 . The method of claim 1 , wherein the medical characteristic is the severity or scope of a medical condition.

7 . The method of claim 1 , further comprising:

determining, by the image processing server using a neural network, the classification of the medical characteristic is relevant to a previous classification made in another instance of medical data received by the image processing server; and

generating, by the image processing server using a neural network, at least one metadata tag that describes a relationship between the two medical characteristic classifications.

8 . The method of claim 1 , wherein the neural network undergoes initial training on a set of example classifications.

9 . The method of claim 1 , further comprising:

receiving, by the image processing server, text associated with the image data;

determining, by the image processing server, that a medical characteristic is described by the text; and

assigning, by the image processing server, a weighting to the medical characteristic described in the text to be used by the neural network when classifying medical characteristics present in the at least one image.

10 . A system, comprising:

at least one processor; and

a memory communicatively coupled to the at least one processor, the memory storing instructions which, when executed by the at least one processor, cause the at least one processor to perform operations comprising:

receiving, medical data including at least one image;

determining, using a neural network, the at least one image within the medical data contains PII;

in response to determining that the at least one image in the medical data contains PII, classifying, by the neural network, at least one medical characteristic of the image;

generating, using the medical characteristic classification, at least one metadata tag that describes the medical characteristic;

modifying, the medical data to replace the image with the generated metadata tag; and

transmitting, the modified medical data.

11 . The system of claim 1 , further comprising:

receiving correction data that indicates a classification, different from the classification determined by the neural network, to be used to generate the at least one metadata tag; and

modifying the at least one metadata tag based on the correction data.

12 . The system of claim 11 , further comprising:

retraining the neural network on the received correction data.

13 . The system of claim 10 , wherein the neural network is trained on previous classifications made in other instances of medical data.

14 . The system of claim 10 , further comprising:

determining the classification of the medical characteristic is relevant to a previous classification made in another instance of medical data received by the image processing server; and

generating at least one metadata tag that describes a relationship between the two medical characteristic classifications.

15 . The system of claim 10 , wherein the medical characteristic is the severity or scope of a medical condition.

16 . The system of claim 10 , wherein the neural network undergoes initial training on a set of example classifications.

17 . The system of claim 10 , further comprising:

receiving text associated with the image data;

determining that a medical characteristic is described by the text; and

assigning a weighting to the medical characteristic described in the text to be used by the neural network when classifying medical characteristics present in the at least one image.

18 . One or more non-transitory computer-readable media storing instructions which, when executed by at least one processor, cause the at least one processor to perform operations comprising:

receiving, medical data including at least one image;

determining, using a neural network, the at least one image within the medical data contains PII;

in response to determining that the at least one image in the medical data contains PII, classifying, by the neural network, at least one medical characteristic of the image;

generating, using the medical characteristic classification, at least one metadata tag that describes the medical characteristic;

modifying, the medical data to replace the image with the generated metadata tag; and

transmitting, the modified medical data.

19 . The media of claim 18 , further comprising:

receiving correction data that indicates a classification, different from the classification determined by the neural network, to be used to generate the at least one metadata tag; and

modifying the at least one metadata tag based on the correction data.

20 . The media of claim 19 , further comprising:

retraining the neural network on the received correction data.