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1. WO2020115747 - SYSTÈME MÉDICAL ROBOTIQUE AYANT DES MODES COLLABORATIFS HUMAINS

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CLAIMS

aim:

1. A system for use in a medical care environment, the system comprising:

a controller, comprising:

(a) a patient collaborative decision-making mode in which the system exchanges data with a patient;

(b) an autonomous decision-making mode in which the system is fully autonomous; and

(c) a doctor collaborative decision-making mode in which the system exchanges data with at least one health care provider;

the controller being configured to alternate among the modes to:

(i) analyze, using artificial intelligence, data obtained from at least one of: the patient, the at least one health care provider, at least one clinical procedure, at least one diagnostic test, or at least one medical database;

(ii) use the analyzed data to select at least one diagnostic test, clinical procedure, or clinical recommendation to be performed by either a health care provider or a medical robot; and

(iii) if indicated by an output from the analyzed data, autonomously instruct the at least one medical robot to perform at least one of a clinical procedure or a diagnostic test; wherein iterative operation of the system, comprising at least one alternation between at least two of the modes, achieves a diagnosis of the patient, and at least one of a treatment plan or instructions to the patient.

2. The system according to claim 1, wherein the controller is further configured to do at least one of:

(i) in the autonomous decision-making mode, improve decision-making capabilities of the robotic control system based on at least one of:

a) the data,

b) statistical analysis performed by the robotic control system, and

c) the diagnostic tests performed by the at least one medical robot;

(ii) in the doctor collaborative mode, incorporate the expertise of the at least one health care provider with the data and with the statistical analysis of the robotic control system to improve collaborative decision-making capabilities; and

(iii) in the patient collaborative mode, output questions to the patient likely to lead an accurate diagnosis,

wherein the learning paths for autonomous mode, doctor collaborative mode, and patient collaborative mode are different.

3. The system according to either of claims 1 or 2, wherein at least one of collected patient data, analyzed information, doctor judgments/decisions, and system judgments/decisions, is available to doctor collaborative mode, patient collaborative mode, and autonomous mode for use in at least one of i) making further judgments/decisions and ii) as training set data for artificial intelligence algorithms.

4. The system according to either of claims 2 or 3, wherein the system is configured to arrive at the same diagnosis for the patient via a first method when the system is in a first mode or first sequential combination of modes, and via a second method when the system is in a second mode or second sequential combination of modes.

5. The system according to any of the previous claims, wherein the robotic control system is configured to provide information to the patient in response to a patient query in at least one of the patient interactive mode and the autonomous mode.

6. The system according to any of the previous claims, wherein the robotic control system in autonomous mode is adapted to exchange analyzed data with, and to learn from, any number of other control systems.

7. The system according to any of the previous claims, wherein the controller is configured to be used in at least one of the modes for long-term patient monitoring in a health care setting.

8. The system according to any of the previous claims, wherein the controller is configured in the autonomous mode to instruct the at least one medical robot to perform any number of diagnostic procedures, comprising at least one of blood drawing, imaging studies, and vital sign acquisition.

9. The system according to any of the previous claims, wherein the controller in the autonomous mode is configured to instruct at least one of the medical robots to perform any number of therapeutic procedures, comprising at least one of prescribing or dispensing medication; providing written or oral instructions; and administering IV fluids.

10. The system according to any of the previous claims, wherein, if iterative sharing of the exchanged, analyzed data between the patient collaborative mode and the autonomous mode results in different output from iterative sharing of the exchanged, analyzed data between the doctor collaborative mode and the autonomous mode, comparison of output from the modes enables achievement of improved diagnostic accuracy.

11. The system according to any of the previous claims, wherein iterative operation of the controller uses artificial intelligence to reach at least one of the diagnosis and the treatment plan, and the patient instructions.

12. The system according to any of the previous claims, wherein the artificial intelligence comprises machine learning.

13. The system according to any of the previous claims, wherein the controller, based on the iterative operation, is configured to switch among the modes, and wherein the decision of at least one of whether to switch to a different mode, when to switch to a different mode, and which mode to switch to, is made by the system using at least collected patient data and artificial intelligence, such that diagnostic accuracy is improved.

14. The system according to any of the previous claims, wherein the instructions to the patient comprise any of: to fill a prescription, to take a prescription, to return for a scheduled follow-up visit, to carry out routine home care tasks, to contact a health care provider, to make an appointment, to allow a medical robot to carry out a test such as blood drawing, to transfer to a different department, or other instructions that are routinely provided to a patient by a human provider in a medical setting.

15. The system according to any of the previous claims, further comprising at least one user interface adapted to exchange the data between the controller and at least one of the patient and the health care provider.

16. The system according to any of the previous claims, wherein said data comprises any of the patient's current age, gender, height, weight, BMI, blood pressure, heart rate, blood laboratory test results, imaging study results, biopsy test results, a previous medical diagnosis, or the patient's past medical data.

17. The system according to any of the previous claims, wherein the analyzing of the data comprises at least one of computational statistics, data mining using exploratory data analysis, or data mining through unsupervised or supervised learning, the data being obtained from at least one of the patient, the health care provider, the patient's previous medical records, the at least one medical database, or previous learning by the robotic control system .

18. The system according to any of the previous claims, wherein the alternation among the modes is determined by the system obtaining maximum data/information from a given mode, whereupon it switches to a different mode, the controller beginning its operation in the patient collaborative mode, switching to the autonomous mode, and, if indicated, switching to the doctor collaborative mode.

19. A method for automated assessment of a patient, comprising the steps of:

i) providing a controller capable of iteratively alternating among three decision-making modes, the modes comprising: a patient information-exchange mode, an autonomous mode, and a health care provider information-exchange mode,

ii) using the controller to obtain data from the patient and from one or more medical databases,

iii) using artificial intelligence and statistical analysis capabilities of the controller, analyzing the data, at least one of the data or the analyzed data being exchanged among at least two of the modes;

iv) using iterative operation of the controller to:

a) in the autonomous decision-making mode, make decisions based on i) the analyzed information and ii) input from at least one of the collaborative modes;

b) in the health care provider information-exchange mode, make decisions based on the analyzed information and incorporating the expertise of at least one health care provider; and

c) in the patient information-exchange mode, output questions, analyze answers provided by the patient, and provide instructions to the patient;

v) performing at least one iterative operation in at least two of the modes; and vi) arriving at a diagnosis of the patient, and at least one of a treatment plan or patient instructions.

20. The method according to claim 19, wherein the controller is further configured to do at least one of:

(i) in the autonomous decision-making mode, improve decision-making capabilities of the robotic control system based on at least one of:

a) the data,

b) statistical analysis performed by the robotic control system, and

c) the diagnostic tests performed by the at least one medical robot;

(ii) in the doctor collaborative mode, incorporate the expertise of the at least one health care provider with the data and with the statistical analysis of the robotic control system to improve collaborative decision-making capabilities; and

(iii) in the patient collaborative mode, output questions to the patient likely to lead to an accurate diagnosis,

wherein the learning paths for autonomous mode, doctor collaborative mode, and patient collaborative mode are different.

21. The method according to either of claims 19 or 20, further comprising the step of providing at least one of the collected patient data, analyzed information, and controller judgments/decisions, to doctor collaborative mode, patient collaborative mode, and autonomous mode for use in at least one of i) making further judgments/decisions and ii) as training set data for artificial intelligence algorithms.

22. A system according to any of claims 19-21, wherein due to different learning paths, the method of arriving at a diagnosis in a first mode or first sequential combination of modes, are different for a second patient with the same symptoms in the same situation.

23. The method according to any of claims 19-22, further comprising the step of providing information to the patient in response to a patient query in at least one of the patient interactive mode and the autonomous mode.

24. The method according to any of claims 19-23, further comprising the step of the controller in autonomous mode exchanging analyzed data with, and learning from, any number of other controllers.

25. The method according to any of claims 19-24, further comprising the step of the controller in autonomous mode instructing at least one medical robot to perform any number of diagnostic procedures, comprising at least one of blood drawing, imaging studies, and vital sign acquisition.

26. The method according to any of claims 19-25, wherein, if iterative exchange of the exchanged, analyzed data between the patient collaborative mode and the autonomous mode results in different output from iterative exchange of the exchanged, analyzed data between the doctor collaborative mode and the autonomous mode, comparison of output from the modes achieves improved diagnostic accuracy.

27. The method according to any of claims 19-26, wherein iterative operation of the controller uses artificial intelligence to reach the diagnosis and the treatment plan, or the patient instructions.

28. The method according to any of claims 19-27, wherein the artificial intelligence comprises machine learning.

29. The method according to any of claims 19-28, wherein the controller, based on the iterative operation, switches among the modes, and wherein the decision of at least one of i) whether to switch to a different mode, ii) when to switch to a different mode, and iii) which mode to switch to, is made by the controller using at least collected patient data and artificial intelligence, such that diagnostic accuracy is improved.

30. The method according to any of claims 19-29, wherein the data comprises any of the patient's current age, gender, height, weight, BMI, blood pressure, heart rate, blood laboratory test results, imaging study results, biopsy test results, a previous medical diagnosis, or the patient's past medical data.

31. The method according to any of claims 19-30, wherein the analyzing of the data comprises at least one of computational statistics, data mining using exploratory data analysis, or data mining through unsupervised learning, the data being obtained from at least one of the patient, the health care provider, the patient's previous medical records, the at least one medical database, or previous learning by the controller.

32. The method according to any of claims 19-31, wherein the alternating among the modes is determined by the controller obtaining maximum data/information from a given mode, whereupon it switches to a different mode, the controller beginning its operation in the patient collaborative mode, switching to the autonomous mode, and, if indicated, switching to the doctor collaborative mode.

33. The system according to claim 19, wherein the diagnosis comprises any one of a provisional diagnosis, a differential diagnosis, or a final diagnosis.

34. The system according to claim 1, wherein for a given patient with given symptoms, a first mode or first sequential combination of modes, and a second mode or a second sequential combination of modes, are configured to perform different methods that are driven by

different optimization goals or optimization strategies yet arrive at the same ultimate treatment plan or diagnosis.

35. The system according to claim 33, wherein the first mode or sequential combination of modes improves diagnosis over time using artificial intelligence according to a first optimization goal or strategy, and wherein the second mode or sequential combination of modes improves methods over time using artificial intelligence according to a second optimization goal or strategy, such that diagnostic accuracy is improved.

36. The system according to any of claims 1-18, wherein the diagnosis comprises any one of a provisional diagnosis, a differential diagnosis, or a final diagnosis.