CN116630534A - Airway management artificial intelligence decision-making system - Google Patents
Airway management artificial intelligence decision-making system Download PDFInfo
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- 210000003437 trachea Anatomy 0.000 claims abstract description 72
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- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H20/00—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance
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- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
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Abstract
The invention discloses an artificial intelligent decision-making system for airway management. The device comprises a patient trachea data acquisition unit, a patient trachea 3D modeling unit, an airway tool judging unit, a trachea cannula assembling unit and a feasibility judging unit. The invention carries out 3D human airway modeling based on the chemicals software and the Simpleware software, and can digitize the human airway of the patient, thereby judging whether the tracheal intubation operation is satisfied according to the numerical value, and further providing accurate guidance for the selection of tracheal intubation, laryngeal masks and mask tools; meanwhile, after the trachea cannula is selected, the trachea cannula can be selected again by means of digitalization of the human airway, and the trachea cannula can be made in the existing parts, so that more accurate establishment of an artificial airway can be provided, and a better treatment effect is provided for a patient.
Description
Technical Field
The invention relates to the technical field of industrial production clamps, in particular to an artificial intelligent decision-making system for airway management.
Background
In the medical field, airway management for critically ill patients includes: airway assessment, oxygen therapy, establishment, maintenance and withdrawal of artificial airways, respiratory support therapy, prevention and treatment of artificial airway complications, and the like. The main purpose of airway management is to prevent and correct hypoxia, sputum drainage, aspiration prevention and the like in patients. Patients with normal respiratory function, such as respiratory center function and normal airway obstruction, can prevent hypoxia by spontaneous breathing or oxygen inhalation by nasal catheter or mask. Patients with cough dysfunction may promote sputum excretion by encouraging cough or assisting in sputum excretion. Patients with severe neurosis often have respiratory central dysfunction, airway obstruction, respiratory insufficiency, etc. to cause or exacerbate hypoxia. These patients must establish an artificial airway and patients with respiratory insufficiency also require mechanical ventilation. The influence of central injury and consciousness disturbance on the airway of the patients suffering from the severe neurosurgery is obvious, and the hypoxia of the patients caused by the unsmooth airway also obviously aggravates the central injury.
Wherein, for neurosurgical severe patients with respiratory central dysfunction, airway obstruction and respiratory dysfunction, an artificial airway must be established because brain tissue is very sensitive to hypoxia. Respiratory center dysfunction, airway obstruction, and respiratory dysfunction all lead to hypoxia in the patient, and an artificial airway must be established immediately. Commonly accepted general indications for endotracheal intubation include airway obstruction, ventilation/oxygenation disorders, predicted worsening of neurological function, predicted worsening of cardiac function, etc. For patients with coma, glasgow Coma Score (GCS) equal to or lower than 8 points, which are caused by craniocerebral injury, cerebrovascular accident, intracranial infection, increased intracranial pressure, etc., an artificial airway should generally be established.
Before performing the tracheal intubation, it should be determined whether the patient has high risk factors of difficult intubation, such as small mandible, limited opening, too small chin-to-tongue distance, etc. Specific evaluation methods can be found in the LEMON method. In preparation for tracheotomy, the necessary evaluation should also be made, such as to confirm whether there is a history of surgery in the neck, whether there is a cervical tumor or thyromegaly, etc. If the above difficult factors exist, a corresponding plan should be made, and further damage to the central nervous system caused by increased craniocerebral pressure, hypoxia and the like due to repeated operation stimulation is avoided. Before establishing an artificial airway, the neural function states of the patient should be evaluated and recorded, including consciousness level, muscular tension, physiological and pathological reflex, and whether there is a skull base fracture, epileptic seizure, instability of the cervical vertebra, and the like. However, the preparation before intubation is usually that a doctor judges the airway condition of a patient according to some data of the patient by virtue of own experience, so that the condition that the tracheal intubation is not properly selected often occurs, and difficult intubation is caused by insufficient evaluation.
Disclosure of Invention
Aiming at the defects in the prior art, the invention aims to provide an airway management artificial intelligence decision system capable of accurately providing the most reasonable airway establishment.
In order to achieve the above purpose, the present invention adopts the following technical scheme:
an airway management artificial intelligence decision making system comprising:
the patient trachea data acquisition unit acquires a complete airway data value of a patient after shooting the chest of a human body through the CT machine;
the patient trachea 3D modeling unit performs 3D modeling of the human airway according to the patient complete airway data value acquired by the patient trachea data acquisition unit through the chemicals software and the simple software to acquire a 3D model corresponding to the patient airway;
the airway tool judging unit analyzes according to the obtained 3D model, evaluates the airway of the patient by means of the numerical value carried by the 3D model, judges that the patient is suitable for a laryngeal mask or a face mask when judging that the airway is abnormal, and selects an endotracheal intubation tool when judging that the airway is normal, wherein the priority order of the tools is endotracheal intubation > laryngeal mask > face mask;
after the tracheal intubation is adopted, the tracheal intubation assembling unit is used for carrying out regional division on the 3D model of a patient according to the data carried by the 3D model, defining the main trachea, the bifurcation part of the bronchus, the left bronchus and the right bronchus as an area A, an area B and an area C, carrying out regional division on the positions of all parts of the tracheal intubation, defining the position of the tracheal intubation for inserting the bronchus as C1, defining the position for inserting the bifurcation part of the bronchus as C2, defining the length of an inlet body of the tracheal intubation as S1, defining the bending angle at the C1 as alpha 1 and defining the bending angle at the C2 as alpha 2, wherein the numerical values corresponding to the C1, the C2, the S1, the alpha 1 and the alpha 2 are respectively obtained according to the data of the area A, the area B, the area C1, the alpha 1 and the alpha 2 in the 3D model, carrying out product assembly of the tracheal intubation in material trousers according to the obtained numerical values corresponding to the numerical values of the C1, the C2, the S1 and the alpha 2, and carrying out packaging after the assembly;
the feasibility judging unit is established before the trachea cannula is assembled in the trachea cannula assembling unit, an existing trachea cannula database is established, the feasibility judging unit pre-establishes products according to the corresponding numerical values of C1, C2, S1, alpha 1 and alpha 2, verifies the pre-established trachea cannula and the existing trachea cannula database, judges whether the pre-established trachea cannula has the corresponding model in the existing trachea cannula database, when the trachea cannula with the corresponding model exists, the product assembling instruction is given, if the trachea cannula with the corresponding model does not exist, the special-shaped trachea cannula is judged, the product assembling instruction is not given, and the prompting of selecting a laryngeal mask or a mask is given.
Preferably, when the airway tool judging unit evaluates the airway of the patient, the airway tool judging unit acquires experience data of past tracheal intubation operation of a doctor responsible for the operation, judges whether the tracheal intubation operation can be completed according to the experience data of the doctor, if so, gives the right to use the tracheal intubation, and if the right exceeds the operation capability range of the doctor, the airway tool judging unit is transferred to the doctor who can complete the tracheal intubation operation, or judges to select a laryngeal mask or a mask.
Preferably, the airway tool judging unit further includes judgment based on LEMON method when making the airway assessment of the patient.
Preferably, in the tracheal cannula assembling unit, the numerical relationships between the area a, the area B, the area C and the areas C1, C2, S1, α1, α2 are as follows: in the 3D model, the size of the A region corresponds to the size of C1, the size of the B region corresponds to the size of C2, the total length span of the A region, the B region and the C region corresponds to the size of S1, the curvature of the C region corresponds to the value of alpha 1, and the curvature of the B region corresponds to the value of alpha 2.
Preferably, when the trachea cannula assembling unit is packaged, the packaging bag is correspondingly marked with the two-dimensional code of the patient information, and after the trachea cannula assembling unit is taken out of the warehouse, a doctor can acquire the patient information of the customized trachea cannula by scanning the two-dimensional code.
Preferably, in the feasibility determining unit, when it is determined that the pre-built tracheal cannula exists in the existing tracheal cannula database, it is determined again whether the doctor responsible for the operation uses the tracheal cannula of the model, when the doctor has a case of successfully using the model, a pass instruction is given to the assembled product, when the doctor does not have a case of successfully using the model, the pass instruction is given to the doctor who can successfully use the model cannula, and when all doctors do not have a case of completing the model cannula in all data, it is determined as the special-shaped tracheal cannula, no product assembly instruction is given, and a prompt for selecting a laryngeal mask or a mask is given.
Preferably, the airway management artificial intelligence decision system can be applied to a field medical platform, is suitable for rescuing soldiers in a battlefield, can perform physical examination of the soldiers in the early stage to acquire CT data corresponding to the soldiers, establishes a 3D model of the airway of the soldiers, numbers the 3D models of the airways of different soldiers one by one, inputs the number corresponding to the soldiers when the airway tool judging unit is required to be rescuing, and converts the number into the corresponding 3D model data for evaluation by the air supply airway tool judging unit.
By adopting the scheme, the invention carries out 3D human airway modeling based on the chemicals software and the Simpleware software, and can digitize the human airway of the patient, thereby judging whether the tracheal intubation operation is satisfied according to the numerical value, and further providing accurate guidance for the selection of tracheal intubation, laryngeal masks and mask tools; meanwhile, after the trachea cannula is selected, the trachea cannula can be selected again by means of digitalization of the human airway, and the trachea cannula can be made in the existing parts, so that more accurate establishment of an artificial airway can be provided, and a better treatment effect is provided for a patient.
Drawings
Fig. 1 is a schematic diagram of the structural principle of an embodiment of the present invention.
FIG. 2 is a schematic diagram of 3D model region partitioning according to an embodiment of the present invention.
Fig. 3 is a schematic view of the division of the tracheal cannula area according to the embodiment of the present invention.
Fig. 4 is a schematic view of an embodiment of the present invention having a tracheal tube inserted into the airway of a human body.
Description of the embodiments
The present invention will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present invention more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
In the description of the present invention, it should be understood that the terms "center", "longitudinal", "lateral", "length", "width", "thickness", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", "clockwise", "counterclockwise", etc. indicate orientations or positional relationships based on the orientations or positional relationships shown in the drawings are merely for convenience in describing the present invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, be configured and operated in a specific orientation, and thus should not be construed as limiting the present invention. Furthermore, the terms "first," "second," and the like, are used for descriptive purposes only and are not to be construed as indicating or implying a relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defining "a first" or "a second" may explicitly or implicitly include one or more of the described features. In the description of the present invention, the meaning of "a plurality" is two or more, unless explicitly defined otherwise.
In the description of the present invention, it should be noted that the terms "mounted," "connected," and "coupled" are to be construed broadly, as well as, for example, fixedly coupled, detachably coupled, or integrally coupled, unless otherwise specifically indicated and defined. Either mechanically or electrically. Can be directly connected or indirectly connected through an intermediate medium, and can be communicated with the inside of two elements or the interaction relationship of the two elements. The specific meaning of the above terms in the present invention can be understood by those of ordinary skill in the art according to the specific circumstances.
As shown in fig. 1 to 4, an artificial intelligence decision system for airway management according to the present embodiment includes:
the patient trachea data acquisition unit acquires a complete airway data value of a patient after shooting the chest of a human body through the CT machine;
the patient trachea 3D modeling unit performs 3D modeling of the human airway according to the patient complete airway data value acquired by the patient trachea data acquisition unit through the chemicals software and the simple software to acquire a 3D model corresponding to the patient airway;
the airway tool judging unit analyzes according to the obtained 3D model, evaluates the airway of the patient according to the numerical value carried by the 3D model, judges that the patient is suitable for a laryngeal mask or a face mask when judging that the airway is abnormal, selects an endotracheal intubation tool when judging that the airway is normal, and selects the tool priority order of the endotracheal intubation > laryngeal mask > face mask, wherein the abnormality is judged according to various data, such as that the glottis of an adult 100kg patient is narrow and the opening angle is smaller, and only 3.0 endotracheal intubation can be passed, but the lower respiratory tract is normal, and 7.0 endotracheal intubation is needed to complete airway sealing ventilation. The system then decides that the patient is not suitable for endotracheal intubation but for laryngeal mask ventilation, while giving the patient a difficult airway case with endotracheal intubation. For example, 50kg of adult patient has narrow glottis and smaller opening angle, and can only pass through 3.0 trachea cannula, but the lower respiratory tract is normal, and the airway sealing ventilation can be completed only by 7.0 trachea cannula, but the patient cannot fully open the mouth and cannot use laryngeal mask, at the moment, the system decides that the patient is not suitable for trachea cannula and laryngeal mask ventilation, and meanwhile, the patient is given a difficult airway case. Mask ventilation is recommended. For another example, an adult 70kg patient has normal upper respiratory tract, but a main bronchus is narrow, and an F37 left double-cavity bronchial cannula is needed, but the front end of the bronchial cannula needs to be customized in length, diameter and blocking balloon position. At this time, the system decision gives the data of the double-cavity trachea cannula which needs to be customized for the patient, and the combination production of parts is arranged;
after the tracheal intubation assembly unit is adopted, according to the data carried by the 3D model, the 3D model of a patient is divided into areas, the main trachea, the bronchus bifurcation, the left bronchus and the right bronchus are defined as an area A, an area B and an area C as shown in fig. 2, the positions of all parts of the tracheal intubation are divided into areas, the position of the tracheal intubation for inserting the bronchus is defined as C1, the position for inserting the bronchus bifurcation is defined as C2, the length of an inlet body of the tracheal intubation is defined as S1, the bending angle at the C1 is defined as alpha 1, the bending angle at the C2 is defined as alpha 2, wherein the values corresponding to the C1, the C2, the S1, the alpha 1 and the alpha 2 are respectively obtained according to the data of the area A, the bronchus bifurcation, the data of the area B and the data of the area C in the 3D model, the products corresponding to the C1, the C2, the S1, the alpha 1 and the alpha 2 are assembled in material trousers, the tracheal intubation corresponding to the products corresponding to the patient are obtained after the assembly is completed, the tracheal intubation is specifically, the C1 is defined as C2, the part C1 and the part alpha 1 is a group of part C1, the part alpha 1 and the part C2 is defined as a part C1 and a part C2;
the feasibility judging unit is established before the trachea cannula is assembled in the trachea cannula assembling unit, an existing trachea cannula database is established, the feasibility judging unit pre-establishes products according to the corresponding numerical values of C1, C2, S1, alpha 1 and alpha 2, verifies the pre-established trachea cannula and the existing trachea cannula database, judges whether the pre-established trachea cannula has the corresponding model in the existing trachea cannula database, when the trachea cannula with the corresponding model exists, the product assembling instruction is given, if the trachea cannula with the corresponding model does not exist, the special-shaped trachea cannula is judged, the product assembling instruction is not given, and the prompting of selecting a laryngeal mask or a mask is given.
It should be noted that, the whole of the embodiment is based on the chemicals software and Simpleware software to perform 3D human airway modeling, and the human airway of the patient can be digitized, so that whether the tracheal intubation operation is satisfied or not is judged according to the numerical value, and further accurate guidance of tracheal intubation, laryngeal mask and mask tool selection is provided; meanwhile, after the trachea cannula is selected, the trachea cannula can be selected again by means of digitalization of the human airway, and the trachea cannula can be made in the existing parts, so that more accurate establishment of an artificial airway can be provided, and a better treatment effect is provided for a patient.
Further, when the airway tool judging unit evaluates the airway of the patient, the airway tool judging unit acquires experience data of past tracheal cannula operation of a doctor in charge of the operation, judges whether the tracheal cannula operation can be completed according to the doctor experience data, gives the right to use the tracheal cannula if the tracheal cannula operation can be completed, and transfers the right to the doctor who can complete the tracheal cannula operation if the right to use the tracheal cannula exceeds the operation capability range of the doctor, or judges to select a laryngeal mask or a mask.
Further, the airway tool judging unit further includes a judgment based on LEMON method when the airway of the patient is evaluated.
Further, in the tracheal cannula assembling unit, the numerical relationships between the A area, the B area and the C1, the C2, the S1, the alpha 1 and the alpha 2 are as follows: in the 3D model, the size of the A region corresponds to the size of C1, the size of the B region corresponds to the size of C2, the total length span of the A region, the B region and the C region corresponds to the size of S1, the curvature of the C region corresponds to the value of alpha 1, and the curvature of the B region corresponds to the value of alpha 2.
Further, when the trachea cannula assembling unit is packaged, the packaging bag is correspondingly provided with the two-dimensional code of the patient information, and after the trachea cannula assembling unit is taken out of the warehouse, a doctor can acquire the patient information of the customized trachea cannula by scanning the two-dimensional code.
Further, in the feasibility judging unit, when judging that the pre-built tracheal cannula exists in the existing tracheal cannula database, judging again whether the doctor responsible for the operation uses the tracheal cannula of the model, when the doctor has the case of successfully using the model, giving a passing instruction of an assembled product, when the doctor does not have the case of successfully using the model, giving the doctor capable of successfully using the model cannula, giving the passing instruction, when all doctors in all data do not have the case of completing the model cannula, judging as the special-shaped tracheal cannula, not giving the product assembling instruction, and giving a prompt of selecting a laryngeal mask or a mask.
Furthermore, the airway management artificial intelligence decision system of the embodiment can be applied to a field medical platform, is suitable for soldier rescue in a battlefield, can perform physical examination of the soldier in the early stage to acquire CT data corresponding to the soldier, establishes a 3D model belonging to the airway of the soldier, numbers the 3D models of the airways of different soldiers one by one, inputs the numbers corresponding to the soldier when the airway tool judging unit is required to be evaluated, and converts the numbers into the corresponding 3D model data for the air supply airway tool judging unit to be evaluated and used.
The foregoing description is only of the preferred embodiments of the present invention, and is not intended to limit the scope of the invention, but rather is intended to cover any equivalents of the structures or equivalent processes disclosed herein or in the alternative, which may be employed directly or indirectly in other related arts.
Claims (7)
1. An airway management artificial intelligence decision making system, characterized in that: comprising the following steps:
the patient trachea data acquisition unit acquires a complete airway data value of a patient after shooting the chest of a human body through the CT machine;
the patient trachea 3D modeling unit performs 3D modeling of the human airway according to the patient complete airway data value acquired by the patient trachea data acquisition unit through the chemicals software and the simple software to acquire a 3D model corresponding to the patient airway;
the airway tool judging unit analyzes according to the obtained 3D model, evaluates the airway of the patient by means of the numerical value carried by the 3D model, judges that the patient is suitable for a laryngeal mask or a face mask when judging that the airway is abnormal, and selects an endotracheal intubation tool when judging that the airway is normal, wherein the priority order of the tools is endotracheal intubation > laryngeal mask > face mask;
after the tracheal intubation is adopted, the tracheal intubation assembling unit is used for carrying out regional division on the 3D model of a patient according to the data carried by the 3D model, defining the main trachea, the bifurcation part of the bronchus, the left bronchus and the right bronchus as an area A, an area B and an area C, carrying out regional division on the positions of all parts of the tracheal intubation, defining the position of the tracheal intubation for inserting the bronchus as C1, defining the position for inserting the bifurcation part of the bronchus as C2, defining the length of an inlet body of the tracheal intubation as S1, defining the bending angle at the C1 as alpha 1 and defining the bending angle at the C2 as alpha 2, wherein the numerical values corresponding to the C1, the C2, the S1, the alpha 1 and the alpha 2 are respectively obtained according to the data of the area A, the area B, the area C1, the alpha 1 and the alpha 2 in the 3D model, carrying out product assembly of the tracheal intubation in material trousers according to the obtained numerical values corresponding to the numerical values of the C1, the C2, the S1 and the alpha 2, and carrying out packaging after the assembly;
the feasibility judging unit is established before the trachea cannula is assembled in the trachea cannula assembling unit, an existing trachea cannula database is established, the feasibility judging unit pre-establishes products according to the corresponding numerical values of C1, C2, S1, alpha 1 and alpha 2, verifies the pre-established trachea cannula and the existing trachea cannula database, judges whether the pre-established trachea cannula has the corresponding model in the existing trachea cannula database, when the trachea cannula with the corresponding model exists, the product assembling instruction is given, if the trachea cannula with the corresponding model does not exist, the special-shaped trachea cannula is judged, the product assembling instruction is not given, and the prompting of selecting a laryngeal mask or a mask is given.
2. An airway management artificial intelligence decision making system according to claim 1 wherein: when the airway tool judging unit evaluates the airway of the patient, the airway tool judging unit acquires experience data of past tracheal intubation operation of a doctor in charge of the operation, judges whether the tracheal intubation operation can be completed according to the doctor experience data, gives the right to use the tracheal intubation if the tracheal intubation operation can be completed, and transfers the right to the doctor who can complete the tracheal intubation operation if the right to use the tracheal intubation exceeds the operation capability range of the doctor, or judges to use a laryngeal mask or a mask.
3. An airway management artificial intelligence decision making system according to claim 2 wherein: the airway tool judging unit further comprises a judgment based on LEMON method when the airway of the patient is evaluated.
4. An airway management artificial intelligence decision making system according to claim 1 wherein: in the trachea cannula assembling unit, the numerical relation between the A area, the B area and the C1, the C2, the S1, the alpha 1 and the alpha 2 is as follows: in the 3D model, the size of the A region corresponds to the size of C1, the size of the B region corresponds to the size of C2, the total length span of the A region, the B region and the C region corresponds to the size of S1, the curvature of the C region corresponds to the value of alpha 1, and the curvature of the B region corresponds to the value of alpha 2.
5. An airway management artificial intelligence decision making system according to claim 1 wherein: when the trachea cannula assembling unit is packaged, the packaging bag is correspondingly provided with the two-dimensional code of the patient information, and after the trachea cannula assembling unit is taken out of the warehouse, a doctor can acquire the patient information of the customized trachea cannula by scanning the two-dimensional code.
6. An airway management artificial intelligence decision making system according to claim 1 wherein: in the feasibility judging unit, when judging that the pre-built trachea cannula exists in the existing trachea cannula database, judging whether a doctor responsible for the operation uses the trachea cannula of the model again, when the doctor has the case of successfully using the model, giving a passing instruction of an assembled product, when the doctor does not have the case of successfully using the model, transferring the passing instruction to the doctor capable of successfully using the model cannula, and when all doctors in all data do not have the case of completing the model cannula, judging that the trachea cannula is abnormal, not giving the product assembling instruction, and giving a prompt of selecting a laryngeal mask or a mask.
7. An airway management artificial intelligence decision making system according to claim 1 wherein: the airway management artificial intelligence decision system can be applied to field medical platform, is suitable for soldier rescue in a battlefield, can carry out physical examination of the soldier in the early stage to acquire CT data corresponding to the soldier, establishes a 3D model belonging to the airway of the soldier, numbers the 3D models of the airways of different soldiers one by one, each number is used for carrying out one 3D model data, when rescue is needed, the number corresponding to the soldier is input when an airway tool judging unit carries out evaluation, and the number is converted into the corresponding 3D model data so as to supply the airway tool judging unit for evaluation.
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Citations (18)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US5135490A (en) * | 1990-12-21 | 1992-08-04 | Strickland Richard D | Method and system for effecting wedging of a bronchoalveolar lavage catheter |
| US20010052344A1 (en) * | 2000-06-16 | 2001-12-20 | Rajiv Doshi | Methods and devices for improving breathing in patients with pulmonary disease |
| US6609521B1 (en) * | 2001-04-09 | 2003-08-26 | Regents Of The University Of Minnesota | Endotracheal tube |
| WO2012017213A1 (en) * | 2010-08-05 | 2012-02-09 | The Laryngeal Mask Company Limited | A laryngeal mask airway device |
| US20120089014A1 (en) * | 2009-06-29 | 2012-04-12 | Koninklijke Philips Electronics N.V. | Method and apparatus for tracking in a medical procedure |
| US20160114116A1 (en) * | 2014-10-27 | 2016-04-28 | Wake Forest University Health Sciences | Low-Profile Bifurcated Bilateral Endotracheal-Endobronchial Tube and Methods of Using |
| CN109003497A (en) * | 2018-07-19 | 2018-12-14 | 苏州敏行医学信息技术有限公司 | airway management training method and system |
| US20200143708A1 (en) * | 2018-11-05 | 2020-05-07 | William OZGA | Method, system, and apparatus for modeling a human trachea |
| CN112370018A (en) * | 2020-11-10 | 2021-02-19 | 皖南医学院第一附属医院（皖南医学院弋矶山医院） | Computer application software for predicting difficult airway and airway management data system |
| CN113413212A (en) * | 2021-06-28 | 2021-09-21 | 哈尔滨理工大学 | Method for automatically intervening bronchoscope in tracheal disease diagnosis and treatment operation |
| CN113781637A (en) * | 2021-09-16 | 2021-12-10 | 华中科技大学 | Method for establishing upper respiratory tract-tracheal tree combined model based on three-dimensional reconstruction |
| CN113891736A (en) * | 2019-03-27 | 2022-01-04 | 巴黎公共救济院 | Method for designing and verifying the shape and position of a cannula for a patient by simulating insertion into the trachea |
| CN114366030A (en) * | 2021-12-31 | 2022-04-19 | 中国科学院苏州生物医学工程技术研究所 | Intelligent auxiliary system and method for anesthesia operation |
| CN115171901A (en) * | 2022-07-27 | 2022-10-11 | 浙江大学医学院附属第一医院 | Intelligent system and method for difficult airway assessment and intraoperative airway management assistance |
| CN115381429A (en) * | 2022-07-26 | 2022-11-25 | 复旦大学附属眼耳鼻喉科医院 | Air flue assessment terminal based on artificial intelligence |
| CN115440374A (en) * | 2022-08-29 | 2022-12-06 | 复旦大学附属眼耳鼻喉科医院 | Air flue collected data management system based on big data warehouse |
| US20230031792A1 (en) * | 2021-08-02 | 2023-02-02 | Zhejiang Haixinzhihui Technology Co., Ltd. | Design Method of Oncological Computerized Physician Order Entry System with Intelligent Clinical Decision Recommendation Function |
| CN115844316A (en) * | 2022-12-30 | 2023-03-28 | 陕西马克医疗科技有限公司 | Difficult airway visual intubation tool for neonatal mandibular malformation |
Patent Citations (18)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US5135490A (en) * | 1990-12-21 | 1992-08-04 | Strickland Richard D | Method and system for effecting wedging of a bronchoalveolar lavage catheter |
| US20010052344A1 (en) * | 2000-06-16 | 2001-12-20 | Rajiv Doshi | Methods and devices for improving breathing in patients with pulmonary disease |
| US6609521B1 (en) * | 2001-04-09 | 2003-08-26 | Regents Of The University Of Minnesota | Endotracheal tube |
| US20120089014A1 (en) * | 2009-06-29 | 2012-04-12 | Koninklijke Philips Electronics N.V. | Method and apparatus for tracking in a medical procedure |
| WO2012017213A1 (en) * | 2010-08-05 | 2012-02-09 | The Laryngeal Mask Company Limited | A laryngeal mask airway device |
| US20160114116A1 (en) * | 2014-10-27 | 2016-04-28 | Wake Forest University Health Sciences | Low-Profile Bifurcated Bilateral Endotracheal-Endobronchial Tube and Methods of Using |
| CN109003497A (en) * | 2018-07-19 | 2018-12-14 | 苏州敏行医学信息技术有限公司 | airway management training method and system |
| US20200143708A1 (en) * | 2018-11-05 | 2020-05-07 | William OZGA | Method, system, and apparatus for modeling a human trachea |
| CN113891736A (en) * | 2019-03-27 | 2022-01-04 | 巴黎公共救济院 | Method for designing and verifying the shape and position of a cannula for a patient by simulating insertion into the trachea |
| CN112370018A (en) * | 2020-11-10 | 2021-02-19 | 皖南医学院第一附属医院（皖南医学院弋矶山医院） | Computer application software for predicting difficult airway and airway management data system |
| CN113413212A (en) * | 2021-06-28 | 2021-09-21 | 哈尔滨理工大学 | Method for automatically intervening bronchoscope in tracheal disease diagnosis and treatment operation |
| US20230031792A1 (en) * | 2021-08-02 | 2023-02-02 | Zhejiang Haixinzhihui Technology Co., Ltd. | Design Method of Oncological Computerized Physician Order Entry System with Intelligent Clinical Decision Recommendation Function |
| CN113781637A (en) * | 2021-09-16 | 2021-12-10 | 华中科技大学 | Method for establishing upper respiratory tract-tracheal tree combined model based on three-dimensional reconstruction |
| CN114366030A (en) * | 2021-12-31 | 2022-04-19 | 中国科学院苏州生物医学工程技术研究所 | Intelligent auxiliary system and method for anesthesia operation |
| CN115381429A (en) * | 2022-07-26 | 2022-11-25 | 复旦大学附属眼耳鼻喉科医院 | Air flue assessment terminal based on artificial intelligence |
| CN115171901A (en) * | 2022-07-27 | 2022-10-11 | 浙江大学医学院附属第一医院 | Intelligent system and method for difficult airway assessment and intraoperative airway management assistance |
| CN115440374A (en) * | 2022-08-29 | 2022-12-06 | 复旦大学附属眼耳鼻喉科医院 | Air flue collected data management system based on big data warehouse |
| CN115844316A (en) * | 2022-12-30 | 2023-03-28 | 陕西马克医疗科技有限公司 | Difficult airway visual intubation tool for neonatal mandibular malformation |
Non-Patent Citations (12)
| Title |
|---|
| 冯洁华，李朝阳，魏宏，张杰，张鹏，罗晓敏，: "3 号、4 号Supreme 喉罩通气罩最大推荐容量半值用于妇科 腹腔镜手术气道管理的研究", 河南医学研究, vol. 26, no. 20, 30 September 2017 (2017-09-30) * |
| 姚远;方政晗;于长久;: "急重症颅脑损伤患者抢救时紧急人工气道的建立及其管理", 创伤外科杂志, no. 08, 15 August 2017 (2017-08-15) * |
| 孙忠朋;陈威威;杨冬;: "CT三维气道重建图像在气道管理中的应用", 医学综述, no. 21, 5 November 2017 (2017-11-05) * |
| 崔建修;徐丽姝;赵国栋;: "CT测量气管内径对双腔支气管插管的指导作用", 南方医科大学学报, no. 10, 20 October 2007 (2007-10-20) * |
| 朱梁;陈紫璇;刘扶摇;张家琛;黄睿;谢冰勇;: "Mimics在关节外科临床教学工作中的应用初探", 中国继续医学教育, no. 16, 10 June 2020 (2020-06-10) * |
| 李孝林;: "基于CT图像应用Mimics软件快速构建人体胸腰段骨骼有限元模型", 中国组织工程研究与临床康复, no. 39, 24 September 2009 (2009-09-24) * |
| 李松青;哈若水;曲爱丽;赵燕玲;封净;杨随兴;张佐;: "阻塞性睡眠呼吸暂停低通气综合征患者的上气道及周围结构三维有限元模型的构建", 宁夏医学杂志, no. 04, 15 April 2010 (2010-04-15) * |
| 汪吉明;黄文;周维肖;: "3D打印技术在处置困难气道中的应用展望", 大众科技, no. 06, 20 June 2017 (2017-06-20) * |
| 谢书奇;张晓庆;郑少强;: "螺旋CT重建成像分析在气管狭窄患者麻醉中的应用", 同济大学学报(医学版), no. 02, 15 April 2011 (2011-04-15) * |
| 谢雨晨;陈文栋;马莉;: "困难气道患者三维有限元模型解剖差异的分析", 中国组织工程研究, no. 04, 20 December 2018 (2018-12-20) * |
| 钟瑞涵，李朝阳，涂汉坤，奉光举，: "Crouzon综合征伴脑积水患者麻醉处理１例", 巴楚医学, vol. 4, no. 3, 30 September 2021 (2021-09-30) * |
| 陈潇君;孙炳伟;苟建平;: "深度机器学习辅助医院智能化管理", 中国现代医学杂志, no. 08, 13 March 2018 (2018-03-13) * |
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