The 2024 National Science and Technology Week and Beijing Science and Technology Week opened in Shougang Park in Shijingshan District from May 25 to June 1.Under the theme of“Carrying forward the spirit of scientists...The 2024 National Science and Technology Week and Beijing Science and Technology Week opened in Shougang Park in Shijingshan District from May 25 to June 1.Under the theme of“Carrying forward the spirit of scientists and inspiring societal innovation,”this event focused on the new-generation IT technology,medical health,energy and technology,modern agriculture and intelligent manufacturing industries.展开更多
Stress concentrations about thin cylindrical shells with small openings are reconsidered front a nerv angle. There is a sort of special internal relation between theoretical solutions about cylindrical shells,vith lar...Stress concentrations about thin cylindrical shells with small openings are reconsidered front a nerv angle. There is a sort of special internal relation between theoretical solutions about cylindrical shells,vith large openings and one,with small openings. Using this relation, the extent of applying the theory about small openings to engineering practice is estimated again, thus an idea of how to use this theory and a nerv appraisal of the application of theoretical solutions about cylindrical shells with small openings to engineering practice are given.展开更多
AIM:To predict cutting formula of small incision lenticule extraction(SMILE)surgery and assist clinicians in identifying candidates by deep learning of back propagation(BP)neural network.METHODS:A prediction program w...AIM:To predict cutting formula of small incision lenticule extraction(SMILE)surgery and assist clinicians in identifying candidates by deep learning of back propagation(BP)neural network.METHODS:A prediction program was developed by a BP neural network.There were 13188 pieces of data selected as training validation.Another 840 eye samples from 425 patients were recruited for reverse verification of training results.Precision of prediction by BP neural network and lenticule thickness error between machine learning and the actual lenticule thickness in the patient data were measured.RESULTS:After training 2313 epochs,the predictive SMILE cutting formula BP neural network models performed best.The values of mean squared error and gradient are 0.248 and 4.23,respectively.The scatterplot with linear regression analysis showed that the regression coefficient in all samples is 0.99994.The final error accuracy of the BP neural network is-0.003791±0.4221102μm.CONCLUSION:With the help of the BP neural network,the program can calculate the lenticule thickness and residual stromal thickness of SMILE surgery accurately.Combined with corneal parameters and refraction of patients,the program can intelligently and conveniently integrate medical information to identify candidates for SMILE surgery.展开更多
文摘The 2024 National Science and Technology Week and Beijing Science and Technology Week opened in Shougang Park in Shijingshan District from May 25 to June 1.Under the theme of“Carrying forward the spirit of scientists and inspiring societal innovation,”this event focused on the new-generation IT technology,medical health,energy and technology,modern agriculture and intelligent manufacturing industries.
文摘Stress concentrations about thin cylindrical shells with small openings are reconsidered front a nerv angle. There is a sort of special internal relation between theoretical solutions about cylindrical shells,vith large openings and one,with small openings. Using this relation, the extent of applying the theory about small openings to engineering practice is estimated again, thus an idea of how to use this theory and a nerv appraisal of the application of theoretical solutions about cylindrical shells with small openings to engineering practice are given.
基金Supported by the National Natural Science Foundation of China(No.82271100)Jiangsu Province Science and Technology Support Plan Project(No.BE2022805).
文摘AIM:To predict cutting formula of small incision lenticule extraction(SMILE)surgery and assist clinicians in identifying candidates by deep learning of back propagation(BP)neural network.METHODS:A prediction program was developed by a BP neural network.There were 13188 pieces of data selected as training validation.Another 840 eye samples from 425 patients were recruited for reverse verification of training results.Precision of prediction by BP neural network and lenticule thickness error between machine learning and the actual lenticule thickness in the patient data were measured.RESULTS:After training 2313 epochs,the predictive SMILE cutting formula BP neural network models performed best.The values of mean squared error and gradient are 0.248 and 4.23,respectively.The scatterplot with linear regression analysis showed that the regression coefficient in all samples is 0.99994.The final error accuracy of the BP neural network is-0.003791±0.4221102μm.CONCLUSION:With the help of the BP neural network,the program can calculate the lenticule thickness and residual stromal thickness of SMILE surgery accurately.Combined with corneal parameters and refraction of patients,the program can intelligently and conveniently integrate medical information to identify candidates for SMILE surgery.
