Cervical cancer and vulva cancer clinical decision-making, teaching and scientific research auxiliary support method and system
A technology for cervical cancer and clinical decision-making, applied in electronic clinical trials, computer-aided medical procedures, informatics, etc., can solve individualized decision-making assistance, lack of teaching and scientific research support, unsystematic analysis, failure to achieve traditional Chinese and Western medicine Combining with other problems to achieve the precise effect of clinical decision support
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Embodiment 1
[0058] In this embodiment, the clinical decision-making, teaching, and scientific research auxiliary support system for cervical cancer and vulvar cancer includes a medical and pharmaceutical data storage unit, a diagnosis and treatment parameter storage unit, an information input unit, a comparison processor unit, a diagnosis and treatment result output unit, and an early warning and monitoring unit. Operation record unit. refer to figure 1 , the specific functions of each constituent unit are as follows:
[0059] Medical and pharmaceutical data storage unit, including: medical and pharmaceutical database, standard clinical pathway and evidence base, real-world clinical pathway and evidence base. The information stored in the medical and pharmaceutical database includes, but is not limited to, medical and pharmaceutical materials of the western medicine system and the traditional Chinese medicine system, medical policy information, structured medical record information, pati...
Embodiment 2
[0073] Based on the system and method implemented in Embodiment 1, specifically refer to Table 1-2, wherein: Table 1 lists some parameters that affect the diagnosis and treatment of cervical cancer, and the parameter values corresponding to each parameter correspond to different parameter values after structured processing Coding; Table 2 lists some of the clinical pathways of cervical cancer expressed in parameter codes.
[0074] Table 1
[0075]
[0076] Table 2
[0077]
[0078] According to Table 1-2, the medical record information of a patient obtained by the information input unit at this time is "a newly diagnosed patient, 30 years old, diagnosed with cervical cancer in our hospital a week ago, assessed as stage IA1 by pathological biopsy, positive for LVSI, and sterile", The patient information parameter value obtained after identification extraction, natural language processing, and rule processing is "newly diagnosed; 30 years old; diagnosed with cervical ...
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