AI-based automatic recognition system of medical text for hypertensive intracerebral hemorrhage

Abstract:

Objective To design an automatic medical text recognition system based on artificial intelligence（AI）， which can quickly spot and analyze patients’ clinical information then output accurate treatment plans.Methods After discussions by senior neurosurgeons and professional AI teams，we designed the automatic recognition and decision-making system of medical text information for hypertensive cerebral hemorrhage（namely H-system） based on the language representation model and the expert mode. Taking the real treatment plans in the database as the gold standard， the accuracy of the H-system was evaluated as a whole，and then it was compared with the senior neurosurgery to analyze the efficiency of the H-system.Results In the testing sets，the accuracy of the output by H-system was 94.0%（91.5%-96.5%），the specificity was 91.8%（86.3%-97.3%），the sensitivity was 95.5%（89.3%-98.2%），and the AUC was 0.936（0.922-0.950）（P=0.000）. Meanwhile，in the validation sets，the accuracy of the output by H-system was 93.3%（89.5%-97.1%），the specificity was 89.9%（83.4%-96.4%），the sensitivity was 95.8%（92.3%-99.3%），and the AUC was 0.928（0.891-0.966）（P=0.000）. In processing the same 70 cases，the H-system took（334.60±4.46） s compared to （12 550.28±95.45） s for the neurosurgeon；in 50 minutes， the H-system processed（383±3） cases compared to （11±4） cases for the neurosurgeon.Conclusion The H-system constructed in this study can automatically recognize and analyze the medical text data of patients， and quickly output an accurate treatment plan. In clinical practice， it may assist doctors to provide an efficient and reliable treatment for patients with hypertensive intracerebral hemorrhage.