Hemorrhagic stroke diagnosis and treatment evaluation system based on data analysis

Abstract

The present invention relates to the field of stroke diagnosis and treatment technology, and discloses a hemorrhagic stroke diagnosis and treatment evaluation system based on data analysis, including a multidimensional acquisition module and an intelligent diagnosis and treatment module. The hemorrhagic stroke diagnosis and treatment evaluation system based on data analysis obtains personal information, treatment data and physical function data of all stroke patients through the multidimensional acquisition module, and classifies and forms a data set. The intelligent diagnosis and treatment module comprehensively analyzes the age, induced diseases and living habits, analyzes the risk of each stroke patient, generates a corresponding risk score, and deeply analyzes individual differences. The intelligent diagnosis and treatment module analyzes the changing trend of the condition of each stroke patient and the risk of hematoma expansion, generates a corresponding fluctuation index and hematoma score, and then analyzes the physical state of each stroke patient's prognosis, generates a corresponding functional data group, judges the patient's stroke risk level and the development trend of the condition, accurately predicts the hematoma expansion trend, and outputs corresponding diagnosis and treatment suggestions.

Description

Technical Field

[0001] The present invention relates to the technical field of stroke diagnosis and treatment, and in particular to a hemorrhagic stroke diagnosis and treatment evaluation system based on data analysis. Background Art

[0002] Hemorrhagic stroke, also known as cerebral hemorrhage or intraparenchymal hemorrhage, is a serious disease caused by the flow of blood into the brain tissue due to the rupture of cerebral blood vessels. This condition is usually caused by high blood pressure, aneurysms or other vascular abnormalities, and manifests as sudden severe headache, nausea and vomiting, and neurological symptoms such as hemiplegia or speech disorders. Headache symptoms are more common in patients with large hematomas, and are aggravated when the hematoma compresses the meningeal pain nerves, the intracranial pressure increases, or blood invades the cerebrospinal fluid. Vomiting is usually related to increased intracranial pressure. Patients with hemorrhagic stroke usually have a decreased level of consciousness due to increased intracranial pressure and compression of the thalamus and brainstem, which may lead to coma in severe cases. This coma symptom is more common in patients with more severe hemorrhagic strokes that endanger the brainstem reticular activating system. About 10% of patients with intracerebral hemorrhage and 50% of patients with lobar hemorrhage report epileptic seizures, and these seizures usually occur within 24 hours after hemorrhagic stroke. Neurological symptoms are common in patients with hemorrhagic stroke and usually worsen within minutes or hours after the onset of hemorrhagic stroke. For example, patients with basal ganglia or supratentorial hemorrhage often have contralateral sensory and motor disorders. Patients with lobar hemorrhage may have symptoms such as aphasia and cortical dysfunction such as gaze deviation. Patients with infratentorial hemorrhage often have symptoms of oculomotor nerve abnormalities and contralateral motor disorders. After hemorrhagic stroke, the expansion of the hematoma is one of the important risk factors for poor prognosis. The range of the hematoma may gradually expand due to factors such as brain tissue damage and inflammatory response, leading to a rapid increase in intracranial pressure, which in turn causes further deterioration of neurological function and even endangers the patient's life. Edema around the hematoma, as a sign of secondary injury after cerebral hemorrhage, may also cause brain tissue compression, thereby affecting neuronal function, further damaging brain tissue, and aggravating the patient's neurological impairment. Therefore, monitoring and controlling the expansion of the hematoma is one of the focuses of clinical attention. Early identification and prediction of the expansion of the hematoma and the occurrence and development of surrounding edema are of great significance for improving the prognosis of patients and improving their quality of life.

[0003] At present, the traditional hemorrhagic stroke diagnosis and treatment evaluation system based on data analysis tends to ignore individual differences when predicting the risk of disease, has difficulty meeting personalized diagnosis and treatment needs, lacks in-depth analysis capabilities, and has difficulty accurately identifying hematoma expansion trends and edema areas, resulting in inaccurate prognostic analysis. Summary of the invention

[0004] 1. Technical issues to be resolved

[0005] In view of the shortcomings of the existing technology, the present invention provides a hemorrhagic stroke diagnosis and treatment evaluation system based on data analysis, which has the advantages of in-depth analysis of individual differences and accurate prediction of hematoma expansion trends. It solves the problem that traditional hemorrhagic stroke diagnosis and treatment evaluation systems based on data analysis are difficult to meet personalized diagnosis and treatment needs and difficult to accurately identify hematoma expansion trends and edema areas.

[0006] (II) Technical solution

[0007] To achieve the above-mentioned purpose, the present invention provides the following technical solutions: a hemorrhagic stroke diagnosis and treatment evaluation system based on data analysis, comprising a multi-dimensional acquisition module and an intelligent diagnosis and treatment module;

[0008] The multi-dimensional acquisition module is composed of a patient data unit, a treatment data unit and a prognosis data unit. The patient data unit is connected to a database via a network to collect a patient data set, and the patient data set includes personal information of all stroke patients. The treatment data unit is connected to an electronic medical record system via a network to collect a treatment data set, and the treatment data set includes treatment data of all stroke patients. The prognosis data unit is connected to an electronic medical record system via a network to collect a prognosis data set, and the prognosis data set includes physical function data of all stroke patients. The multi-dimensional acquisition module transmits the patient data set, the treatment data set and the prognosis data set to the intelligent diagnosis and treatment module via the network.

[0009] The intelligent diagnosis and treatment module consists of a basic analysis unit, a disease analysis unit and a diagnosis and treatment evaluation unit. The basic analysis unit analyzes the risk of each stroke patient based on the patient data set and generates a corresponding risk score. The condition analysis unit is provided with a monitoring cycle of fixed duration. and fixed range volume thresholds , combined with the treatment data set, analyze the changing trend of each stroke patient's condition and the risk of hematoma expansion, and generate the corresponding fluctuation index and hematoma score The diagnosis and treatment evaluation unit is set with a fixed range of functional thresholds , platelet threshold and thrombin threshold , combined with the prognostic data set, analyze the physical status of each stroke patient's prognosis and generate the corresponding functional data set The diagnosis and treatment assessment unit is set with a fixed range of risk thresholds , combined with the risk score , Volatility Index and hematoma score , determine the patient's stroke risk level and disease development trend, and output corresponding diagnosis and treatment recommendations.

[0010] Preferably, the expression of the patient data set is , to First to Second The personal information of stroke patients includes age, gender, causative diseases and lifestyle habits. Represents the duration of illness of a single stroke patient.

[0011] Preferably, the expression of the treatment data set is , to First to Second The treatment data of stroke patients included Hunt-Hess score, NIHSS score, Fisher score, hematoma volume, hematoma morphology and hematoma location. Indicates the specific time when the patient treatment data is obtained.

[0012] Preferably, the expression of the prognosis data set is , to First to Second The physical function data of stroke patients included Fugl-Meyer score, platelet count and thrombin time. Indicates the specific time when the patient's physical function data is obtained.

[0013] Preferably, the risk score The calculation process is as follows:

[0014] Extract the patient data set The personal information of stroke patients will be The age of the stroke patients was marked as , will The sex of the stroke patients was marked as , will The causative diseases of stroke patients were labeled , will The lifestyle habits of stroke patients were marked as ;

[0015] like For men,

[0016] ;

[0017] like For women,

[0018] ;

[0019] In the formula, represents the risk score, represents the weight for the age of stroke patients, represents the weight of the causative diseases for stroke patients, represents the weight of the living habits of stroke patients, represents the additional points for male stroke patients. , , and are all constants, among which, ,like For men, Indicates according to , and The weight is combined with age, predisposing diseases, lifestyle habits and extra points to get the first The risk score of stroke patients is For women, Indicates according to , and The weights are combined with age, predisposing diseases and lifestyle habits to obtain the Risk scores for stroke patients.

[0020] Preferably, the volatility index The calculation process is as follows:

[0021] Extract monitoring cycles based on treatment data set During the period treatment data of stroke patients and monitor the period During the period, The Hunt-Hess score of stroke patients is marked as , to Respectively Stroke patients from the first time point to the The Hunt-Hess score at each time point will be monitored during the During the period, The NIHSS scores of stroke patients were marked as , to Respectively Stroke patients from the first time point to the The NIHSS score at each time point will be monitored during the During the period, The Fisher score of stroke patients is marked as , to Respectively Stroke patients from the first time point to the Fisher score at each time point;

[0022] ;

[0023] ;

[0024] ;

[0025] ;

[0026] In the formula, represents the volatility index, Indicates monitoring cycle During the period, The mean value of Hunt-Hess score in stroke patients , Indicates monitoring cycle During the period, The average NIHSS score of stroke patients , Indicates monitoring cycle During the period, The average Fisher score of stroke patients , , and The monitoring cycle During the period, The maximum Hunt-Hess score, the maximum NIHSS score, and the maximum Fisher score of the stroke patients. Indicates Hunt-Hess score at each time point, Indicates NIHSS scores at each time point, Indicates Fisher scores at each time point, According to the variance formula, the variance value is The fluctuation index of Hunt-Hess score in stroke patients, According to the variance formula, the variance value is Fluctuation index of NIHSS score in stroke patients, According to the variance formula, the variance value is Fluctuation index of Fisher score in stroke patients.

[0027] Preferably, the hematoma score The calculation process is as follows:

[0028] Extract monitoring cycles based on treatment data set During the period treatment data of stroke patients and The hematoma volume of the stroke patients was marked as , will The hematoma morphology of stroke patients was marked as , will The location of the hematoma in the stroke patient is marked as ;

[0029] like Exceeding volume threshold When the volume score Score 1 point;

[0030] like Irregular geometric shape, morphological score Score 1 point;

[0031] like Located in the brainstem, location score It is scored as 2 points;

[0032] like Located in the cerebellum, ventricles, thalamus, subarachnoid space, or basal ganglia, location score Score 1 point;

[0033] ;

[0034] In the formula, It represents the hematoma score, which includes volume score, morphology score and location score.

[0035] Preferably, the functional data set The calculation process is as follows:

[0036] Extract the prognostic data set The physical function data of stroke patients were The Fugl-Meyer score for the prognosis of stroke patients is marked as , will Platelet count markers for prognosis in stroke patients , will The prognostic marker of thrombin time in stroke patients is ;

[0037] ;

[0038] In the formula, Indicates the functional data group, and Functional Threshold The minimum and maximum values ​​in Indicates that the Fugl-Meyer score and functional threshold for prognosis in stroke patients , and Platelet threshold The minimum and maximum values ​​in Indicates that the Platelet counts versus platelet thresholds for prognosis in stroke patients , and Thrombin threshold The minimum and maximum values ​​in Indicates that the Prognostic significance of thrombin time versus thrombin threshold in stroke patients .

[0039] Preferably, the risk score Exceeding risk threshold It indicates that the risk level of stroke patient is high and the patient is advised to take timely precautions against hemorrhagic stroke.

[0040] Preferably, the monitoring period During this period, the volatility index The maximum values ​​of Hunt-Hess score, NIHSS score, and Fisher score in the If any of the values ​​in the above table continues to rise, it means that the condition of the stroke patient has worsened. It is recommended that medical staff should adjust the patient's condition according to the functional data group. Develop a diagnosis and treatment plan.

[0041] Compared with the prior art, the present invention provides a hemorrhagic stroke diagnosis and treatment evaluation system based on data analysis, which has the following beneficial effects:

[0042] 1. The present invention connects the database and the electronic medical record system through a multi-dimensional acquisition module network to obtain the personal information, treatment data and physical function data of all stroke patients, and classifies them into patient data sets, treatment data sets and prognosis data sets. The intelligent diagnosis and treatment module analyzes the risk of each stroke patient based on the patient data set, comprehensive age, induced diseases and living habits, and generates a corresponding risk score , and deeply analyze individual differences.

[0043] 2. The present invention sets a monitoring cycle with a fixed duration through the intelligent diagnosis and treatment module and fixed range volume thresholds , combined with the treatment data set, analyze the changing trend of each stroke patient's condition and the risk of hematoma expansion, and generate the corresponding fluctuation index and hematoma score , deeply analyze the changing trends of various indicators. The larger the fluctuation, the more unstable the patient's condition. Then analyze the physical condition of each stroke patient's prognosis and generate the corresponding functional data set The worse the physical function of the patient, the more targeted the treatment intensity needs to be adjusted. The intelligent diagnosis and treatment module sets a fixed range of risk thresholds. , combined with the risk score , Volatility Index and hematoma score , determine the patient's stroke risk level and disease development trend, accurately predict the hematoma expansion trend, and output corresponding diagnosis and treatment recommendations. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Figure 1 It is a schematic diagram of the system flow of the present invention. DETAILED DESCRIPTION

[0045] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0046] Because the traditional hemorrhagic stroke diagnosis and treatment evaluation system based on data analysis tends to ignore individual differences when predicting the risk of disease, it is difficult to meet the needs of personalized diagnosis and treatment, lacks in-depth analysis capabilities, and is difficult to accurately identify the hematoma expansion trend and edema area, resulting in inaccurate prognosis analysis. Therefore, a hemorrhagic stroke diagnosis and treatment evaluation system based on data analysis is provided. Please refer to Figure 1 ,The system includes a multi-dimensional acquisition module and an intelligent diagnosis and treatment module;

[0047] The multidimensional acquisition module consists of a patient data unit, a treatment data unit, and a prognosis data unit. The patient data unit collects patient data sets through a network connection database. The patient data set includes the personal information of all stroke patients. The expression of the patient data set is , to First to Second The personal information of stroke patients includes age, gender, causative diseases and lifestyle habits. It indicates the duration of illness of a single stroke patient. With the increase of age, the blood vessel walls of the human body gradually age, the elasticity of blood vessels decreases, the fragility increases, atherosclerosis is more likely to occur, the metabolic rate will also be significantly reduced, and the blood circulation will slow down. These factors lead to a higher risk of stroke.

[0048] The treatment data unit collects the treatment data set through the network connection electronic medical record system. The treatment data set includes the treatment data of all stroke patients. The expression of the treatment data set is , to First to Second The treatment data of stroke patients included Hunt-Hess score, NIHSS score, Fisher score, hematoma volume, hematoma morphology and hematoma location. Indicates the specific time when the patient's treatment data was obtained. The Hunt-Hess score, NIHSS score, and Fisher score are all scales used in the medical field to assess the severity or prognosis of a disease. The hematoma characteristics intuitively reflect the expansion trend and edema area;

[0049] The prognosis data unit collects the prognosis data set through the network connection electronic medical record system. The prognosis data set includes the physical function data of all stroke patients. The expression of the prognosis data set is , to First to Second The physical function data of stroke patients included Fugl-Meyer score, platelet count and thrombin time. Indicates the specific time when the patient's physical function data is obtained;

[0050] The multi-dimensional acquisition module transmits the patient data set, treatment data set and prognosis data set to the intelligent diagnosis and treatment module through the network;

[0051] The intelligent diagnosis and treatment module consists of a basic analysis unit, a disease analysis unit, and a diagnosis and treatment evaluation unit. The basic analysis unit analyzes the risk of each stroke patient based on the patient data set and generates a corresponding risk score. , the calculation process is as follows:

[0052] Extract the patient data set The personal information of stroke patients will be The age of the stroke patients was marked as , will The sex of the stroke patients was marked as , will The causative diseases of stroke patients were labeled , if the patient has hypertension, atherosclerosis and diabetes, That is 1, the The lifestyle habits of stroke patients were marked as If the patient drinks, smokes and stays up late for a long time, That is 1;

[0053] like Men have higher levels of androgen, which can promote the occurrence and development of atherosclerosis. Bad habits such as smoking and drinking are also more common in men.

[0054] ;

[0055] like For women,

[0056] ;

[0057] In the formula, represents the risk score, represents the weight for the age of stroke patients, represents the weight of the causative diseases for stroke patients, represents the weight of the living habits of stroke patients, represents the additional points for male stroke patients. , , and are all constants, among which, ,like For men, Indicates according to , and The weight is combined with age, predisposing diseases, lifestyle habits and extra points to get the first The risk score of stroke patients is For women, Indicates according to , and The weights are combined with age, predisposing diseases and lifestyle habits to obtain the The risk scores of stroke patients were analyzed in depth to analyze individual differences;

[0058] The condition analysis unit is set with a fixed-duration monitoring cycle and fixed range volume thresholds , combined with the treatment data set, analyze the changing trend of each stroke patient's condition and the risk of hematoma expansion, and generate the corresponding fluctuation index and hematoma score , the calculation process is as follows:

[0059] Extract monitoring cycles based on treatment data set During the period treatment data of stroke patients and monitor the period During the period, The Hunt-Hess score of stroke patients is marked as , to Respectively Stroke patients from the first time point to the The Hunt-Hess score at each time point will be monitored during the During the period, The NIHSS scores of stroke patients were marked as , to Respectively Stroke patients from the first time point to the The NIHSS score at each time point will be monitored during the During the period, The Fisher score of stroke patients is marked as , to Respectively Stroke patients from the first time point to the Fisher score at each time point;

[0060] ;

[0061] ;

[0062] ;

[0063] ;

[0064] In the formula, represents the volatility index, Indicates monitoring cycle During the period, The mean value of Hunt-Hess score in stroke patients , Indicates monitoring cycle During the period, The average NIHSS score of stroke patients , Indicates monitoring cycle During the period, The average Fisher score of stroke patients , , and The monitoring cycle During the period, The maximum Hunt-Hess score, the maximum NIHSS score, and the maximum Fisher score of the stroke patients. Indicates Hunt-Hess score at each time point, Indicates NIHSS scores at each time point, Indicates Fisher scores at each time point, According to the variance formula, the variance value is The fluctuation index of Hunt-Hess score in stroke patients, According to the variance formula, the variance value is Fluctuation index of NIHSS score in stroke patients, According to the variance formula, the variance value is The fluctuation index of Fisher score of stroke patients was analyzed in depth, and the changing trend of each index was analyzed. The larger the fluctuation, the more unstable the patient's condition.

[0065] Extract monitoring cycles based on treatment data set During the period treatment data of stroke patients and The hematoma volume of the stroke patients was marked as , will The hematoma morphology of stroke patients was marked as , will The location of the hematoma in the stroke patient is marked as ;

[0066] like Exceeding volume threshold When the volume score Score 1 point;

[0067] like Irregular geometric shape, morphological score Score 1 point;

[0068] like Located in the brainstem, location score It is scored as 2 points;

[0069] like Located in the cerebellum, ventricles, thalamus, subarachnoid space, or basal ganglia, location score Score 1 point;

[0070] ;

[0071] In the formula, It represents the hematoma score, which includes volume score, morphology score and location score;

[0072] The diagnostic and assessment unit is set with a fixed range of functional thresholds , platelet threshold and thrombin threshold , combined with the prognostic data set, analyze the physical status of each stroke patient's prognosis and generate the corresponding functional data set , the calculation process is as follows:

[0073] Extract the prognostic data set The physical function data of stroke patients were The Fugl-Meyer score for the prognosis of stroke patients is marked as , will Platelet count markers for prognosis in stroke patients , will The prognostic marker of thrombin time in stroke patients is ;

[0074] ;

[0075] In the formula, Indicates the functional data group, and Functional Threshold The minimum and maximum values ​​in Indicates that the Fugl-Meyer score and functional threshold for prognosis in stroke patients , and Platelet threshold The minimum and maximum values ​​in Indicates that the Platelet counts versus platelet thresholds for prognosis in stroke patients , and Thrombin threshold The minimum and maximum values ​​in Indicates that the Prognostic significance of thrombin time versus thrombin threshold in stroke patients , the worse the physical function of the patient, the more targeted the treatment intensity needs to be adjusted;

[0076] The diagnosis and treatment assessment unit has a fixed range of risk thresholds , combined with the risk score , Volatility Index and hematoma score , determine the patient's stroke risk level and disease development trend, and output corresponding diagnosis and treatment recommendations, risk score Exceeding risk threshold When the patient has a high risk of developing a stroke, it is recommended that the patient take timely precautions against hemorrhagic stroke and monitor the period During this period, the volatility index The maximum values ​​of Hunt-Hess score, NIHSS score, and Fisher score in the If any of the values ​​in the data set continues to rise, it means that the condition of the stroke patient is getting worse. It can accurately predict the hematoma expansion trend and suggest that medical staff should follow the functional data set to Develop a diagnosis and treatment plan.

[0077] Example 1: In this experiment, a male stroke patient was selected as the experimental subject. According to statistics, the patient was 60 years old, the induced disease was hypertension, and his lifestyle included long-term drinking and smoking. The risk score of the male stroke patient was The calculation formula is as follows:

[0078] ;

[0079] In the formula, represents the risk score, represents the weight for the age of stroke patients, represents the weight of the causative diseases for stroke patients, represents the weight of the living habits of stroke patients, represents the additional points for male stroke patients. , , and are all constants, among which, ,according to , and The risk score of this male stroke patient is obtained by combining age, predisposing diseases, lifestyle habits and additional points. .

[0080] Example 2: In this experiment, a stroke patient who had received a complete treatment plan was selected as the experimental subject. After testing, the patient's Fugl-Meyer score was 86 points, platelet count was 100,000 / μl, thrombin time was 15 seconds, and functional threshold The platelet threshold is 90-100 points. The thrombin threshold is 150,000-350,000 / μl. The patient's functional data set is 16-18 seconds. The calculation formula is as follows:

[0081] ;

[0082] In the formula, Indicates the functional data group, The Fugl-Meyer score indicating the prognosis of the stroke patient is below the functional threshold , The platelet count indicating the prognosis of this stroke patient is below the platelet threshold , The thrombin time indicating the prognosis of the stroke patient is lower than the thrombin threshold .

[0083] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A hemorrhagic stroke diagnosis and treatment evaluation system based on data analysis, characterized by: Including multi-dimensional acquisition module and intelligent diagnosis and treatment module; The multi-dimensional acquisition module is composed of a patient data unit, a treatment data unit and a prognosis data unit. The patient data unit is connected to a database via a network to collect a patient data set, and the patient data set includes personal information of all stroke patients. The treatment data unit is connected to an electronic medical record system via a network to collect a treatment data set, and the treatment data set includes treatment data of all stroke patients. The prognosis data unit is connected to an electronic medical record system via a network to collect a prognosis data set, and the prognosis data set includes physical function data of all stroke patients. The multi-dimensional acquisition module transmits the patient data set, the treatment data set and the prognosis data set to the intelligent diagnosis and treatment module via the network. The intelligent diagnosis and treatment module consists of a basic analysis unit, a disease analysis unit and a diagnosis and treatment evaluation unit. The basic analysis unit analyzes the risk of each stroke patient based on the patient data set and generates a corresponding risk score. The condition analysis unit is provided with a monitoring cycle of fixed duration. and fixed range volume thresholds , combined with the treatment data set, analyze the changing trend of each stroke patient's condition and the risk of hematoma expansion, and generate the corresponding fluctuation index and hematoma score The diagnosis and treatment evaluation unit is set with a fixed range of functional thresholds , platelet threshold and thrombin threshold , combined with the prognostic data set, analyze the physical status of each stroke patient's prognosis and generate the corresponding functional data set The diagnosis and treatment assessment unit is set with a fixed range of risk thresholds , combined with the risk score , Volatility Index and hematoma score , determine the patient's stroke risk level and disease development trend, and output corresponding diagnosis and treatment recommendations.

2. The hemorrhagic stroke diagnosis and treatment evaluation system based on data analysis according to claim 1 is characterized in that: Expression for the patient dataset , to First to Second The personal information of stroke patients includes age, gender, causative diseases and lifestyle habits. Represents the duration of illness of a single stroke patient.

3. The hemorrhagic stroke diagnosis and treatment evaluation system based on data analysis according to claim 2 is characterized in that: The expression of the treatment data set is , to First to Second The treatment data of stroke patients included Hunt-Hess score, NIHSS score, Fisher score, hematoma volume, hematoma morphology and hematoma location. Indicates the specific time when the patient treatment data is obtained.

4. The hemorrhagic stroke diagnosis and treatment evaluation system based on data analysis according to claim 3 is characterized in that: The expression of the prognosis dataset is: , to First to Second The physical function data of stroke patients included Fugl-Meyer score, platelet count and thrombin time. Indicates the specific time when the patient's physical function data is obtained.

5. The hemorrhagic stroke diagnosis and treatment evaluation system based on data analysis according to claim 4 is characterized in that: The risk score The calculation process is as follows: Extract the patient data set The personal information of stroke patients will be The age of the stroke patients was marked as , will The sex of the stroke patients was marked as , will The causative diseases of stroke patients were labeled , will The lifestyle habits of stroke patients were marked as ; like For men, ； like For women, ； In the formula, represents the risk score, represents the weight for the age of stroke patients, represents the weight of the causative diseases for stroke patients, represents the weight of the living habits of stroke patients, represents the additional points for male stroke patients. , , and are all constants, among which, ,like For men, Indicates according to , and The weight is combined with age, predisposing diseases, lifestyle habits and extra points to get the first The risk score of stroke patients is For women, Indicates according to , and The weights are combined with age, predisposing diseases and lifestyle habits to obtain the Risk scores for stroke patients.

6. The hemorrhagic stroke diagnosis and treatment evaluation system based on data analysis according to claim 5 is characterized in that: The volatility index The calculation process is as follows: Extract monitoring cycles based on treatment data set During the period Treatment data of stroke patients and monitoring period During the period, The Hunt-Hess score of stroke patients is marked as , to Respectively Stroke patients from the first time point to the The Hunt-Hess score at each time point will be monitored during the During the period, The NIHSS scores of stroke patients were marked as , to Respectively Stroke patients from the first time point to the The NIHSS score at each time point will be monitored during the During the period, The Fisher score of stroke patients is marked as , to Respectively Stroke patients from the first time point to the Fisher score at each time point; ； ； ； ； In the formula, represents the volatility index, Indicates monitoring cycle During the period, The mean value of Hunt-Hess score in stroke patients , Indicates monitoring cycle During the period, The average NIHSS score of stroke patients , Indicates monitoring cycle During the period, The average Fisher score of stroke patients , , and Monitoring cycle During the period, The maximum Hunt-Hess score, the maximum NIHSS score and the maximum Fisher score of the stroke patients. Indicates Hunt-Hess score at each time point, Indicates NIHSS scores at each time point, Indicates Fisher scores at each time point, According to the variance formula, the variance value is The fluctuation index of Hunt-Hess score in stroke patients, According to the variance formula, the variance value is Fluctuation index of NIHSS score in stroke patients, According to the variance formula, the variance value is Fluctuation index of Fisher score in stroke patients.

7. The hemorrhagic stroke diagnosis and treatment evaluation system based on data analysis according to claim 6 is characterized in that: The hematoma score The calculation process is as follows: Extract monitoring cycles based on treatment data set During the period treatment data of stroke patients and The hematoma volume of the stroke patients was marked as , will The hematoma morphology of stroke patients was marked as , will The location of the hematoma in the stroke patient is marked as ; like Exceeding volume threshold When the volume score Score 1 point; like Irregular geometric shape, morphological score Score 1 point; like Located in the brainstem, location score It is scored as 2 points; like Located in the cerebellum, ventricles, thalamus, subarachnoid space, or basal ganglia, location score Score 1 point; ； In the formula, It represents the hematoma score, which includes volume score, morphology score and location score.

8. The hemorrhagic stroke diagnosis and treatment evaluation system based on data analysis according to claim 7 is characterized in that: The performance data set The calculation process is as follows: Extract the prognostic data set The physical function data of stroke patients were The Fugl-Meyer score for the prognosis of stroke patients is marked as , will Platelet count markers for prognosis in stroke patients , will The prognostic marker of thrombin time in stroke patients is ; ； In the formula, Indicates the functional data group, and Functional Threshold The minimum and maximum values ​​in Indicates that the Fugl-Meyer score and functional threshold for prognosis in stroke patients , and Platelet threshold The minimum and maximum values ​​in Indicates that the Platelet counts versus platelet thresholds for prognosis in stroke patients , and Thrombin threshold The minimum and maximum values ​​in Indicates that the Prognostic significance of thrombin time versus thrombin threshold in stroke patients .

9. The hemorrhagic stroke diagnosis and treatment evaluation system based on data analysis according to claim 8, characterized in that: The risk score Exceeding risk threshold It indicates that the risk level of stroke patient is high and the patient is advised to take timely precautions against hemorrhagic stroke.

10. The hemorrhagic stroke diagnosis and treatment evaluation system based on data analysis according to claim 9, characterized in that: The monitoring period During this period, the volatility index The maximum values ​​of Hunt-Hess score, NIHSS score, and Fisher score in the If any of the values ​​in the above table continues to rise, it means that the condition of the stroke patient has worsened. It is recommended that medical staff should adjust the patient's condition according to the functional data group. Develop a diagnosis and treatment plan.

Images