Ai-based stroke treatment workflow improvement cloud system

Abstract

The present invention relates to an AI-based stroke treatment workflow improvement cloud system, which comprises: a medical data reception unit for receiving, from the picture archiving and communications system (PACS) of a local hospital, a medical image of a stroke patient and patient information; an AI analysis unit for analyzing the medical image of the stroke patient by using AI; and an analysis result provision unit for providing, to a regional center server, an AI analysis result obtained by using AI to analyze the medical image of the stroke patient, wherein the analysis result provision unit provides the AI analysis result to a user terminal of medical staff so as to receive the patient information through the user terminal.

Description

A cloud system that improves AI-based stroke treatment workflows.

[0001] The present invention relates to an artificial intelligence-based stroke treatment workflow improvement cloud system, and more specifically, to an artificial intelligence-based stroke treatment workflow improvement cloud system that enables faster response and treatment of stroke patients by simultaneously transferring the patient to a stroke treatment center and preparing for treatment when a stroke patient occurs.

[0002] Typically, stroke patients visit a local hospital and undergo procedures such as registering in the hospital records, taking a CT scan, and interpreting images. If a transfer is decided, the same procedures are repeated at the regional center.

[0003] In this way, because there is no data sharing system between hospitals, unnecessary duplicate procedures are repeated, and procedures are performed serially, which causes delays in the time until treatment for stroke patients.

[0004] This can cause the golden time in stroke treatment to be missed, as the patient's prognosis can vary significantly depending on the timing of treatment after onset.

[0005] Therefore, improvements in the conventional stroke treatment workflow are needed to enable more rapid response and treatment of stroke patients.

[0006] The present invention has been devised to solve the aforementioned problem, and according to the present invention, by sharing patient information, medical images, and artificial intelligence analysis results between a local hospital and a regional center (stroke specialized treatment center), there is no need to retake images at the regional center (stroke specialized treatment center) because images taken at the local hospital exist, thereby shortening the time until interpretation.

[0007] In addition, according to the present invention, it is intended to enable medical staff to check the patient's real-time status and data on user terminals such as mobile phones and PCs, so that they can quickly and easily check the patient's status without location constraints and respond to a treatment call in advance before the patient arrives at the hospital.

[0008] In addition, according to the present invention, it is intended to treat stroke patients more quickly by enabling medical staff to share necessary data in advance, thereby enabling them to perform tasks that need to be performed before the procedure in parallel while the patient is being transferred to a regional center (stroke treatment center).

[0009] According to an embodiment of the present invention for solving the above-described problem, a cloud system for improving an AI-based stroke treatment workflow includes a medical data receiving unit for receiving medical images and patient information of a stroke patient from a PACS (Picture Archiving and Communications System) of a regional hospital; an AI analysis unit for analyzing the medical images of the stroke patient using AI; and an analysis result providing unit for providing the AI ​​analysis result of analyzing the medical images of the stroke patient using AI to a regional center server; wherein the analysis result providing unit provides the AI ​​analysis result to a user terminal of a medical staff so that the patient information is provided through the user terminal.

[0010] According to another embodiment of the present invention, the AI ​​analysis unit can determine an emergency patient in a state of caution by analyzing in real time the status of the stroke patient input and updated through the user terminal.

[0011] According to another embodiment of the present invention, the analysis result providing unit may provide the artificial intelligence analysis result obtained by analyzing the medical image of the stroke patient using artificial intelligence to an external server of the regional center.

[0012] According to another embodiment of the present invention, the AI ​​analysis unit can analyze the medical images of the stroke patient using a plurality of artificial intelligence models to generate a stroke full cycle analysis result including prediction of the urgency and prognosis of the stroke patient.

[0013] According to another embodiment of the present invention, the present invention may further include a push notification provision unit that sends a notification of a stroke patient to the user terminal of a medical staff when a patient suspected of having a stroke is identified.

[0014] According to the present invention, since patient information, medical images, and artificial intelligence analysis results are shared between a local hospital and a regional center (stroke specialized treatment center), there is no need to retake images at the regional center (stroke specialized treatment center) because images taken at the local hospital exist, thereby shortening the time until interpretation.

[0015] In addition, according to the present invention, since the real-time status and data of a patient can be checked on user terminals such as mobile phones and PCs, medical staff can quickly and easily check the patient's status without location constraints and respond to a treatment call in advance before the patient arrives at the hospital.

[0016] In addition, since the present invention allows medical staff to receive necessary data in advance, tasks to be performed before the procedure can be performed in parallel while the patient is being transferred to a regional center (stroke treatment center), thereby enabling stroke patients to be treated more quickly.

[0017] FIG. 1 is a diagram illustrating an artificial intelligence-based stroke treatment workflow improvement cloud system according to one embodiment of the present invention.

[0018] FIG. 2 is a configuration diagram of an artificial intelligence-based stroke treatment workflow improvement cloud system according to one embodiment of the present invention.

[0019] FIG. 3 is a flowchart of a stroke treatment method improved by an artificial intelligence-based stroke treatment workflow improvement cloud system according to an embodiment of the present invention.

[0020] The present invention is susceptible to various modifications and embodiments. Specific embodiments are illustrated in the drawings and described in detail in the detailed description. However, this is not intended to limit the present invention to specific embodiments, but rather to encompass all modifications, equivalents, and alternatives falling within the spirit and technical scope of the present invention.

[0021] However, when describing embodiments, if a detailed description of a related known function or configuration is judged to unnecessarily obscure the gist of the present invention, a detailed description thereof will be omitted. Furthermore, the sizes of each component in the drawings may be exaggerated for illustrative purposes and do not necessarily represent the sizes actually applied.

[0022] Additionally, throughout the specification, when a component is referred to as being "connected" or "connected" to another component, it should be understood that the component may be directly connected or connected to the other component, but may also be connected or connected via another component in between, unless otherwise specifically stated. Additionally, throughout the specification, when it is said that a part "includes" a component, this does not exclude other components, but rather includes other components, unless otherwise specifically stated.

[0023] FIG. 1 is a diagram illustrating an AI-based stroke treatment workflow improvement cloud system according to one embodiment of the present invention. FIG. 2 is a configuration diagram of an AI-based stroke treatment workflow improvement cloud system according to one embodiment of the present invention.

[0024] Hereinafter, an artificial intelligence-based stroke treatment workflow improvement cloud system according to an embodiment of the present invention will be described with reference to FIGS. 1 and 2.

[0025] An artificial intelligence-based stroke treatment workflow improvement cloud system (120) according to an embodiment of the present invention may be configured as a cloud server, and referring to FIG. 1, an artificial intelligence-based stroke treatment workflow improvement cloud system (120) according to an embodiment of the present invention receives medical images and patient information of a stroke patient from a PACS (Picture Archiving and Communications System: 110) of a local hospital.

[0026] In addition, the above artificial intelligence-based stroke treatment workflow improvement cloud system (120) analyzes the medical images of the stroke patient using artificial intelligence.

[0027] To explain in more detail, the artificial intelligence-based stroke treatment workflow improvement cloud system (120) can analyze the status of the stroke patient input and updated through the user terminal in real time to determine an emergency patient in a state of caution.

[0028] Accordingly, the above-described artificial intelligence-based stroke treatment workflow improvement cloud system (120) can provide the results of the artificial intelligence analysis of the medical images of the stroke patient using artificial intelligence to the regional center server (130).

[0029] More specifically, the artificial intelligence-based stroke treatment workflow improvement cloud system (120) provides the artificial intelligence analysis results to the medical staff's user terminal, thereby providing the patient information through the user terminal.

[0030] In addition, the above-mentioned artificial intelligence-based stroke treatment workflow improvement cloud system (120) can also provide the artificial intelligence analysis results obtained by analyzing the medical images of the stroke patient using artificial intelligence to an external server of the regional center.

[0031] Referring to FIG. 2, the artificial intelligence-based stroke treatment workflow improvement cloud system (120) may be configured to include a medical data receiving unit (121), an AI analysis unit (122), an analysis result providing unit (123), and a push notification providing unit (124).

[0032] The above medical data receiving unit (121) receives medical images and patient information of a stroke patient from the PACS (Picture Archiving and Communications System) of a local hospital.

[0033] Accordingly, the AI ​​analysis unit (122) analyzes the medical image of the stroke patient using artificial intelligence.

[0034] At this time, the AI ​​analysis unit (122) can analyze the status of the stroke patient, which is input and updated through the user terminal, in real time to determine an emergency patient in a state of caution.

[0035] The above analysis result provision unit (123) analyzes the medical image of the stroke patient using artificial intelligence and provides the artificial intelligence analysis result to the regional center server (130).

[0036] More specifically, the analysis result provision unit (123) can provide the artificial intelligence analysis result to a medical staff user terminal, thereby allowing the patient information to be provided through the user terminal.

[0037] In addition, the above analysis result provision unit (123) can also provide the artificial intelligence analysis result obtained by analyzing the medical image of the stroke patient using artificial intelligence to an external server of the regional center.

[0038] In addition, the AI ​​analysis unit (122) can analyze the medical images of the stroke patient using multiple artificial intelligence models to generate a full stroke cycle analysis result including prediction of the urgency and prognosis of the stroke patient.

[0039] Accordingly, the analysis result provision unit (123) can provide the entire stroke periodic analysis results including the urgency and prognosis prediction of the stroke patient to the regional center server (130), and can provide the patient information through the user terminal.

[0040] In addition, the push notification provision unit (124) can send a notification of a stroke patient to the medical staff's user terminal when a patient suspected of having a stroke is identified.

[0041] Through this, according to the present invention, patient information, medical images, and artificial intelligence analysis results are shared between local hospitals and regional centers (stroke specialized treatment centers), so there is no need to retake images at the regional center (stroke specialized treatment center) because images taken at the local hospital exist, thereby shortening the time until interpretation.

[0042] In addition, according to the present invention, since the real-time status and data of a patient can be checked on user terminals such as mobile phones and PCs, medical staff can quickly and easily check the patient's status without location constraints and respond to a treatment call in advance before the patient arrives at the hospital.

[0043] In addition, since the present invention allows medical staff to receive necessary data in advance, tasks to be performed before the procedure can be performed in parallel while the patient is being transferred to a regional center (stroke treatment center), thereby enabling stroke patients to be treated more quickly.

[0044]

[0045] FIG. 3 is a flowchart of a stroke treatment method improved by an artificial intelligence-based stroke treatment workflow improvement cloud system according to an embodiment of the present invention.

[0046] Hereinafter, with reference to FIG. 3, a stroke treatment method improved by an artificial intelligence-based stroke treatment workflow improvement cloud system according to an embodiment of the present invention will be described.

[0047] When a patient develops stroke symptoms (S201), he / she visits a local hospital (S202), registers as a stroke patient at the local hospital (S203), takes a CT scan, and the medical image of the CT scan is registered in the PACS (Picture Archiving and Communications System) of the local hospital (S204).

[0048] Accordingly, the stroke treatment workflow improvement cloud system receives medical images and patient information of the stroke patient from the PACS, analyzes the medical images of the stroke patient using artificial intelligence, and provides and shares the results of the artificial intelligence analysis to a regional center server (S205).

[0049] Accordingly, the transfer of the stroke patient is decided based on the results of analyzing the medical images of the stroke patient (S211), and the stroke patient is transferred to a regional center (stroke specialized treatment center) (S212).

[0050] At the same time, the regional center (stroke specialized treatment center) receives the medical images and patient information of the stroke patient from the PACS through the stroke treatment workflow improvement cloud system, so the stroke patient can be registered at the hospital without having to retake the images of the stroke patient (S221).

[0051] Therefore, since the patient's real-time status and data can be checked on user terminals such as mobile and PC, the medical staff can quickly and easily check the patient's status without location constraints, assemble the treatment team in advance before the patient arrives at the hospital (S222), and perform revascularization surgery upon the stroke patient's arrival (S223) (S224).

[0052] In this way, according to the present invention, since medical staff can receive necessary data in advance, they can perform tasks that need to be performed before the procedure in parallel while the patient is being transferred to a regional center (stroke treatment center), thereby enabling stroke patients to be treated more quickly.

[0053] Furthermore, according to the present invention, medical staff or paramedics can upload patient information and share it with relevant medical staff in real time. Therefore, hospitals can access real-time patient information, enabling workflows to run in parallel even during stroke patient transport, thereby eliminating and streamlining redundant tasks during inter-hospital transfers.

[0054] In addition, according to the present invention, a real-time chat function is provided through a user terminal, so that medical staff can collaborate or communicate through the real-time chat function, and a viewer function is provided through the user terminal, so that when a registered patient takes a medical image, the medical image and the artificial intelligence analysis result are uploaded to the cloud, so that the medical staff can check the medical image on the mobile APP of the user terminal or the viewer on the PC web.

[0055] In addition, according to the present invention, by providing a push notification function when a suspected patient is found as a result of an AI analysis, when a medical image is taken at a hospital, an AI analysis is performed, and when a patient suspected of having a stroke is identified as a result of the AI ​​analysis, a push notification is provided to the user terminal of the relevant medical staff, allowing the medical staff to more quickly identify a stroke patient and make a decision.

[0056] At this time, according to the present invention, by utilizing multiple artificial intelligence models, it supports periodic analysis results before stroke, from hyperacute to prognostic prediction, and analysis results appropriate to the situation can help medical staff make quick and accurate judgments.

[0057] The detailed description of the present invention, as described above, has described specific embodiments. However, various modifications are possible without departing from the scope of the present invention. The technical spirit of the present invention should not be limited to the aforementioned embodiments, but should be defined not only by the claims but also by equivalents thereof.

Claims

1. A medical data receiving unit that receives medical images and patient information of stroke patients from the PACS (Picture Archiving and Communications System) of a local hospital; An AI analysis unit that analyzes the medical images of the above stroke patient using artificial intelligence; and An analysis result provision unit that analyzes the medical images of the above stroke patient using artificial intelligence and provides the results of the artificial intelligence analysis to the regional center server; Including, The above analysis results provider is, An artificial intelligence-based stroke treatment workflow improvement cloud system characterized in that the results of the artificial intelligence analysis are provided to a medical staff user terminal, thereby allowing the medical staff to receive the patient information through the user terminal.

2. In claim 1, The above AI analysis unit, An artificial intelligence-based stroke treatment workflow improvement cloud system characterized in that it analyzes in real time the status of the stroke patient input and updated through the user terminal and determines the status of the emergency patient in a state of caution.

3. In claim 1, The above analysis results provider is, An artificial intelligence-based stroke treatment workflow improvement cloud system characterized by providing the results of artificial intelligence analysis of the medical images of the above stroke patient to an external server of a regional center.

4. In claim 1, The above AI analysis unit, An artificial intelligence-based stroke treatment workflow improvement cloud system characterized in that it analyzes the medical images of the stroke patient using multiple artificial intelligence models to generate a stroke full cycle analysis result including prediction of the urgency and prognosis of the stroke patient.

5. In claim 1, A push notification provision unit that sends a notification of a stroke patient to the medical staff's user terminal when a patient suspected of having a stroke is identified; An artificial intelligence-based stroke treatment workflow improvement cloud system characterized by further including:

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