Systems and methods for processing and analyzing medical data
Described herein are apparatuses (e.g., systems, devices) and methods for processing, distributing, and analyzing medical data. In particular, apparatuses and methods for processing and distributing tasks or jobs for completion by a qualified worker or specialist are described. Crowdsourcing data to specialists for interpretation can be accomplished using an auction system to match the specialists with discrete portions of the data. The data can be bundled based on one or more categories or characteristics, and then placed on an auction where the specialists can bid for each bundle by submitting a payment price. The data can be medical data, such as ECG data, imaging data and test data.
1. A method for analyzing ECG data, the method comprising:
receiving ECG data from a plurality of users in a server having a processor and memory;
categorizing, using the processor, the ECG data into groups based on extracted ECG features;
listing the categorized ECG groups by category on an online auction house;
receiving bids for the listed ECG groups from registered specialists;
determining, using the processor, which specialist won a bid for a group from the listed ECG groups;
providing the specialist that won the bid for the group with access to the ECGs within the group; and
inserting at least one reference ECG in each ECG group; determining an accuracy of the received interpreted ECG data based on the specialists' interpretation of the reference ECG; and re-listing the group of ECGs on the online auction house when the accuracy is below a predetermined threshold.
2. The method of claim 1 , further comprising receiving interpreted ECG data from the specialist for the ECGs within the group.
3. The method of claim 1 , further comprising extracting, using the processor, a plurality of ECG features from the ECG data.
4. The method of claim 1 , wherein receiving comprises receiving ECG data including extracted ECG features from the plurality of users.
5. The method of claim 1 , wherein categorizing comprises categorizing the ECG data into groups based on extracted ECG features including location information.
6. The method of claim 1 , wherein categorizing comprises categorizing the ECG data into groups based on extracted ECG features including user annotations.
7. The method of claim 1 , wherein categorizing comprises categorizing the ECG data into groups based on extracted ECG features including one or more of: amplitude, polarity, duration, or shape of the P, Q, R, S and T waves and QRS complex; ratios and amplitude differences between P, Q, R, S and T waves, or QRS complex; beat to beat variability between P, Q, R, S and T waves, or QRS complex; P-R interval; QRS interval; Q-T interval; S-T interval; P-R segment; S-T segment; and beat to beat frequency.
8. The method of claim 1 , further comprising inserting at least one reference ECG in each ECG group.
9. The method of claim 1 , further comprising inserting at least one reference ECG in each ECG group; and determining an accuracy of the received interpreted ECG data based on the specialists' interpretation of the reference ECG.
10. The method of claim 1 , further comprising notifying a user that the user's ECG data has been interpreted.
11. The method of claim 1 , further comprising providing a user with a list of local specialists based on location information provided with ECG data from the user.
12. The method of claim 1 , further comprising storing the ECG data and the interpreted ECG data in a database.
13. A method for analyzing ECG data, the method comprising:
receiving ECG data from a plurality of users in a server having a processor and memory;
categorizing, using the processor, the ECG data into groups based on extracted ECG features;
listing the categorized ECG groups by category on an online auction house;
receiving bids for the listed ECG groups from registered specialists;
determining, using the processor, which specialist won a bid for a group from the listed ECG groups;
providing the specialist that won the bid for the group with access to the ECGs within the group; and
duplicating a user's ECG data between two or more groups; and re-listing the two or more groups of ECGs on the online auction house when the agreement between the interpreted ECG data for the duplicated ECG data is below a predetermined threshold.
14. A method for analyzing ECG data, the method comprising:
receiving ECG data from a plurality of users in a server having a processor and memory;
categorizing, using the processor, the ECG data into groups based on extracted ECG features;
listing the categorized ECG groups by category on an online auction house;
receiving bids for the listed ECG groups from registered specialists;
determining, using the processor, which specialist won a bid for a group from the listed ECG groups;
providing the specialist that won the bid for the group with access to the ECGs within the group; and
scheduling an appointment for a user, using the processor, with a local specialist.
15. A non-transitory computer-readable storage medium storing a set of instructions capable of being executed by a processor, that when executed by the processor causes the processor to:
receive ECG data from a plurality of ECG recording devices;
categorize the ECG data into a plurality of groups based on extracted ECG features;
list the ECG groups by category on an online auction house;
receive bids for the listed ECG groups from registered specialists;
determine which specialist won a bid for a group from the listed ECG groups;
provide the specialist that won the bid for the group with access to the ECGs within the group; and
wherein the set of instructions, when executed by the processor, further causes the processor to determine an accuracy for the specialist and re-list the ECG group on the online auction house if the accuracy is below a threshold.
16. The non-transitory computer-readable storage medium of claim 15 , wherein the set of instructions, when executed by the processor, further causes the processor to receive interpreted ECG data from the specialists.
17. The non-transitory computer-readable storage medium of claim 15 , wherein the set of instructions, when executed by the processor, further causes the processor to determine an accuracy for the specialist.
18. The non-transitory computer-readable storage medium of claim 15 , wherein the set of instructions, when executed by the processor, further causes the processor to determine an accuracy for the specialist by inserting at least one reference ECG in each ECG group.
19. The non-transitory computer-readable storage medium of claim 15 , wherein the set of instructions, when executed by the processor, further causes the processor to extract a plurality of ECG features from the received ECG data.
20. The non-transitory computer-readable storage medium of claim 15 , wherein the set of instructions, when executed by the processor, further causes the processor to categorize the ECG data into a plurality of groups based on extracted ECG features including location information.
21. The non-transitory computer-readable storage medium of claim 15 , wherein the set of instructions, when executed by the processor, further causes the processor to categorize the ECG data into a plurality of groups based on extracted ECG features including user annotations.
22. The non-transitory computer-readable storage medium of claim 15 , wherein the set of instructions, when executed by the processor, further causes the processor to categorize the ECG data into a plurality of groups based on extracted ECG features including one or more of: amplitude, polarity, duration, or shape of the P, Q, R, S and T waves and QRS complex; ratios and amplitude differences between P, Q, R, S and T waves, or QRS complex; beat to beat variability between P, Q, R, S and T waves, or QRS complex; P-R interval; QRS interval; Q-T interval; S-T interval; P-R segment; S-T segment; and beat to beat frequency.
23. The non-transitory computer-readable storage medium of claim 15 , wherein the set of instructions, when executed by the processor, further causes the processor to notify a user that the user's ECG data has been interpreted.
24. The non-transitory computer-readable storage medium of claim 15 , wherein the set of instructions, when executed by the processor, further causes the processor to store the ECG data and the interpreted ECG data in a database.
25. A non-transitory computer-readable storage medium storing a set of instructions capable of being executed by a processor, that when executed by the processor causes the processor to:
receive ECG data from a plurality of ECG recording devices;
categorize the ECG data into a plurality of groups based on extracted ECG features;
list the ECG groups by category on an online auction house;
receive bids for the listed ECG groups from registered specialists;
determine which specialist won a bid for a group from the listed ECG groups;
provide the specialist that won the bid for the group with access to the ECGs within the group; and
wherein the set of instructions, when executed by the processor, further causes the processor to provide a user with a list of local specialists based on location information provided with ECG data from the user.
26. A non-transitory computer-readable storage medium storing a set of instructions capable of being executed by a processor, that when executed by the processor causes the processor to:
receive ECG data from a plurality of ECG recording devices;
categorize the ECG data into a plurality of groups based on extracted ECG features;
list the ECG groups by category on an online auction house;
receive bids for the listed ECG groups from registered specialists;
determine which specialist won a bid for a group from the listed ECG groups;
provide the specialist that won the bid for the group with access to the ECGs within the group; and
wherein the set of instructions, when executed by the processor, further causes the processor to schedule an appointment for a user, using the processor, with a local specialist.