The present invention provides a learning system for clinical diagnosis which comprises (a) at least one learning operation device, (b) a database device, (c) a server device and (d) at least one patient simulator device, and provides a user with training for clinical diagnosis based on a real disease case. The present invention further provides a learning method and steps for clinical diagnosis thereof.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A learning system for clinical diagnosis, comprising: (a) at least one learning operation device, comprising a display element, an output element and an input element, wherein the output element outputs a disease case setting of a user, and the user inputs information relating to the diagnosis via the input element; (b) a database device for storing at least one information of a disease case and a preset clinical diagnosis operating parameter corresponding to the disease case; (c) a server device, being connected to the at least one learning operation device and the database device in a wireless or wired manner, for receiving the disease case setting of the user sent by the at least one learning operation device, comparing a corresponding information of the disease case stored in the database device, and delivering the corresponding information of the disease case to the at least one learning operation device and a patient simulator device; and (d) the at least one patient simulator device, being connected to the server device in a wireless or wired manner and comprising at least one detection component and at least one simulation component, for receiving the information of the disease case sent by the server device, in which the at least one simulation component exhibits at least one simulated physiological message corresponding to the disease case, and the at least one detection component detects a clinical diagnosis operation performed on the patient simulator device by the user, generates a clinical diagnosis operation parameter of the user and delivers it to the server device, wherein the at least one learning operation device delivers the disease case setting of the user to the server device via the output element, receives the corresponding information of the disease case from the server device, compares a clinical diagnosis command with the information of the disease case from the server device based on the clinical diagnosis command inputted by the user via the input element, displays compared result by the display element, and delivers the clinical diagnosis command of the user to the server device via the output element, and wherein the server device receives and records the clinical diagnosis command of the user from the at least one learning operation device and the clinical diagnosis operation parameter of the user sent by the at least one patient simulator device, compares the same with the preset operating parameter of clinical diagnosis corresponding to the disease case stored in the database device, and then determines accuracy. 2. The learning system of the claim 1, wherein the at least one patient simulator device and the at least one learning operation device record the clinical diagnosis operation parameter and the clinical diagnosis command of the user, respectively. 3. The learning system of the claim 1, wherein the device generates a score result according to the accuracy of the clinical diagnosis relative information of the user. 4. The learning system of the claim 3, wherein the learning operation device further comprises an accessing element for accessing the score result generated by the server device, and the clinical diagnosis operation parameter and clinical diagnosis command of the user stored in the server device. 5. The learning system of the claim 1, wherein the sever device is further equipped with a clinical diagnosis learning software. 6. The learning system of the claim 5, wherein the clinical diagnosis learning software is DxR Clinician. 7. The learning system of the claim 1, further comprising a wireless base device, connected to the server device, for generating a wireless transmitting environment, wherein the server device connects to other devices wirelessly via the wireless base device. 8. The learning system of the claim 1, wherein the at least one learning operation device is a computer, a portable computer, a tablet computer, an iPad or a cellular phone. 9. The learning system of the claim 1, wherein the shape of the patient simulator device imitates a human structure. 10. The learning system of the claim 1, wherein the at least one learning operation device comprises a learning operation device for a student and a monitoring device for a director, in which the learning operation device for the student is used for inputting the clinical diagnosis command and displaying the information of the disease case and score result, and the monitoring device for the director is used for inputting the disease case setting, accessing and analyzing the score result generated by the server device, and the clinical diagnosis operation parameter, and the clinical diagnosis command of the user stored in the server device, and updating the data stored in the database device. 11. The learning system of the claim 1, wherein the information of the disease case is a medical record, at least one disease symptom, an inquiry response of patient, a physical examination result, a clinical examination datum, or a physical response message. 12. The learning system of the claim 1, wherein the preset clinical diagnosis operating parameter is a preset inquiry item and response, a preset physical examination, a preset clinical examination item, an interpretation result of the preset clinical examination item, a preset diagnostic result or a preset treatment result. 13. The learning system of the claim 1, wherein the detection component is used to detect sound, light, touch, pressing or temperature of clinical diagnosis operation performed on the patient simulator device by the user. 14. The learning system of the claim 1, wherein the simulation component is used for simulating the sound, jitter, temperature or action corresponding to diseases. 15. The learning system of the claim 1, further comprising a clinical diagnosis operation device for receiving a detection signal for the physical examination from the patient simulator device. 16. The learning system of the claim 15, wherein the detection signal is heart sound or lung sound. 17. The learning system of the claim 1, wherein the clinical diagnosis operation parameter of the user includes the location, time, step and operation time of the physique examination item. 18. The learning system of the claim 1, wherein the clinical diagnosis command is an inquiry item and response, a physical examination, a clinical examination item, an interpretation of the clinical examination item, a diagnostic result, a treatment result, or cost and operation time of a clinical diagnosis operation. 19. The learning system of the claim 18, wherein the clinical examination item is an imaging examination, an electrocardiography examination or a specimen biochemical examination. 20. A learning method for clinical diagnosis applying the learning system for clinical diagnosis of claim 1, in which the learning system comprises at least one learning operation device, a database device, a server device and at least one patient simulator device, the method comprising the steps of: (a) inputting a disease case setting into the at least one learning operation device by a user; (b) delivering the disease case setting to the server device by the at least one learning operation device; (c) receiving the disease case setting and comparing the disease case setting with corresponding information of the disease case stored in the database device, and delivering the comparison to the at least one learning operation device and the at least one patient simulator device by the server device; (d) exhibiting at least one simulated physiological message corresponding to the information of the disease case by the at least one patient simulator device; (e) performing a clinical diagnosis operation on the at least one patient simulator device based on the at least one simulated physiological message, and inputting a clinical diagnosis command, using the at least one learning operation device, by the user; (f) detecting the clinical diagnosis operation of the user, generating a clinical diagnosis operation parameter of the user, and delivering it to the server device by the at least one patient simulator device; (g) comparing by the at least one learning operation device the inputted clinical diagnosis command with the information of the disease case sent by the server device based on the inputted clinical diagnosis command, displaying the comparison by the display element, and delivering the clinical diagnosis command of the user to the server device by the at least one learning operation device; and (h) via the server device, receiving and recording the clinical diagnosis command of the user sent back by the at least one learning device, and the clinical diagnosis operation parameter of the user sent back by the at least one patient simulator device, comparing the same with the preset operating parameter of clinical diagnosis corresponding to the disease case stored in the database device, and then determining accuracy. 21. The learning method of the claim 20, wherein the at least one patient simulator device and the at least one learning operation device record the clinical diagnosis operation parameter and the clinical diagnosis command of the user, respectively. 22. The learning method of the claim 20, wherein the server device generates a score result according to the accuracy of the clinical diagnosis related information of the user. 23. The learning method of the claim 22, wherein the learning operation device further comprises an accessing element for accessing the score result generated by the server device, and the clinical diagnosis operation parameter and clinical diagnosis command of the user stored in the server device. 24. The learning method of the claim 20, wherein the sever device is further equipped with a clinical diagnosis learning software. 25. The learning method of the claim 24, wherein the clinical diagnosis learning software is DxR Clinician. 26. The learning method of the claim 20, which further comprises a wireless base device, connected to the server device, for generating a wireless transmitting environment, wherein the server device connects to other devices wirelessly via the wireless base device. 27. The learning method of the claim 20, wherein the at least one learning operation device comprises a learning operation device for a student and a monitoring device for a director, in which the learning operation device for the student is used for inputting the clinical diagnosis command and displaying the information of a disease case and score result, wherein the monitoring device for the director is used for inputting the disease case setting, storing and analyzing the score result generated by the server device and the clinical diagnosis operation parameter and the clinical diagnosis command stored in the server device, and updating the data stored in the database device. 28. The learning method of the claim 20, wherein the information of the disease case is a medical record, at least one disease symptom, an inquiry response of patient, a physical examination result, a clinical examination datum, or a physical response signal. 29. The learning method of the claim 20, wherein the preset operating parameter of clinical diagnosis is a preset inquiry item and response, a preset physical examination, a preset clinical examination item, a interpretation result of the preset clinical examination item, a preset diagnostic result or a preset treatment result. 30. The learning method of the claim 20, wherein the detection component is used to detect sound, light, touch, pressing or temperature of clinical diagnosis operation performed on the patient simulator device by the user. 31. The learning method of the claim 20, wherein the simulation component is used for simulating the sound, jitter, temperature or action corresponding to diseases. 32. The learning method of the claim 20, wherein the clinical diagnosis operation parameter of the user is location, time, step and operation time of the physical examination item. 33. The learning method of the claim 20, wherein the clinical diagnosis command is an inquiry item and response, a clinical examination item, an interpretation of the clinical examination item, a diagnostic result, a treatment result or cost and operation time of a clinical diagnosis operation. 34. The learning method of the claim 33, wherein the clinical examination item is an imaging examination, an electrocardiography examination or a specimen biochemical examination.