ABSTRACT
OBJECTIVE To evaluate the safety and suitability of traditional Chinese medicine prescriptions generated by generative artificial intelligence （AIGC）， and to provide research ideas for empowering the traditional Chinese medicine industry with AIGC. METHODS Using the 2020 edition of Chinese Pharmacopoeia and the 5th edition of Traditional Chinese Medicine as corpus， GPT-4 and the real-time networking model developed based on GPT-4 （referred to as the “networking model”） were used for deep learning. The clinical cases included in the consensus of traditional Chinese medicine experts in recent years were extracted manually to regenerate prescriptions based on diagnosis using the GPT-4 model and networking model； traditional Chinese medicine experts conducted blind evaluation and scoring of GPT-4 generated prescriptions， networking model generated prescriptions， and expert consensus prescriptions. At the same time， Turing testing was used to evaluate whether the GPT-4 model and networking model had the same ability as human intelligence. RESULTS The average score of traditional Chinese medicine prescriptions generated by the GPT-4 model showed no statistically significant difference compared to manual prescriptions （P＞0.05）， while the average score of prescriptions generated by the networking model showed no statistically significant difference compared to traditional Chinese medicine prescriptions generated by the GPT-4 model （P＞0.05）. The proportion of model-generated prescriptions mistakenly judged as manual prescriptions in the Turing test was 51.11%. CONCLUSIONS The traditional Chinese medicine prescriptions generated by the GPT-4 model have reached a certain level of safety and suitability， and the GPT-4 model has passed the Turing test. The introduction of AIGC in the diagnosis and treatment process may provide technical support for the rational use of clinical traditional Chinese medicine.
ABSTRACT
Objective:To evaluate the efficacy and mechanism of continuous blood purification(CBP) in the treatment of severe sepsis in children.Methods:A total of 42 patients with severe sepsis were enrolled in the study.According to the parents undefined desire to treatment, on the basis of the same treatment condition, 30 cases in the blood purification group were treated with CBP, and 12 cases in the control group were given the routine treatment without CBP treatment.The difference of each index between the two groups at the baseline(before treatment) and 72 hours after treatment were observed.Results:The differences of heart rate, mean arterial pressure and brain natriuretic peptide before and after treatment in the blood purification group were significantly higher than those in control group( P<0.05), and the differences of oxygenation index, 24-hour average urine volume, blood urea nitrogen, creatinine and Glasgow coma score in the blood purification group were significantly higher than those in control group( P<0.05). The difference of capillary refill time, lactic acid and central venous oxygen saturation in blood purification group were significantly higher than those in control group( P<0.05). The level of white blood cell count, C-reactive protein, procalcitonin and interleukin-6 in blood purification group were significantly higher than those in control group, with all significant difference( P<0.05). There was significant difference in critical illness score between two groups after treatment and before treatment.The mortality rate of the blood purification group was significantly lower than that in control group( P<0.01). Conclusion:CBP can improve cardiovascular function, brain function, renal function, tissue perfusion, inflammation index, internal environment, and improve the score of children with severe sepsis.