Lung cancer clinical decision-making, teaching and scientific research auxiliary support system and method
A technology for clinical decision-making and auxiliary support, applied in electronic clinical trials, computer-aided medical procedures, informatics, etc., can solve the problem of individual decision-making assistance, lack of teaching and scientific research support, inability to assist in clinical diagnosis and treatment, and failure to achieve Chinese and Western medicine. Combined with other problems, to achieve the effect of accurate clinical decision support
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Embodiment 1
[0057] In this embodiment, the lung cancer clinical decision-making, teaching, and scientific research auxiliary support system 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 operation recording unit. refer to figure 1 , the specific functions of each constituent unit are as follows:
[0058] 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, patient out-of-hospital management informatio...
Embodiment 2
[0072] 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 lung cancer, and the parameter values corresponding to each parameter are coded corresponding to different parameter values after structured processing; Table 2 lists some of the clinical pathways of lung cancer represented by parameter codes.
[0073]
[0074] Table 1
[0075] Table 2
[0076] According to Table 1-2, the medical record information of a patient acquired by the information input unit at this time is "a newly diagnosed patient, 50 years old, diagnosed with small cell lung cancer in our hospital 10 days ago, and evaluated by imaging examination as limited stage I (T1 , N0, M0), mediastinal pathological stage is negative", the patient information parameter value obtained after identification extraction, natural language processing, and rule processing is "new treatment; 50 ye...
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