Proceedings of the 1st International Symposium on Artificial Intelligence in Medical Sciences最新文献

{"title":"Correlation between the incidence of ischemic stroke and the changes of 24 solar terms in Fuzhou","authors":"Hui-ling Huang, Chi Chen, Feifei Chen, Zhihui Huang, Xiaomin Zhu, Hui Wang","doi":"10.1145/3429889.3430084","DOIUrl":"https://doi.org/10.1145/3429889.3430084","url":null,"abstract":"Objective: Stroke is one of the major diseases that have endangered human health since modern times. With the development of society, the incidence of stroke has only risen. A large number of research data show that the onset of stroke is inseparable from meteorological changes. 24 solar terms are the product of Chinese civilization. It is a knowledge system created by our ancestors following the agricultural time by observing the movement of celestial bodies and cognizing the changing laws of time, climate, phenology and other aspects of the year. This study explored the relationship between the twenty-four solar terms and their changes and the peak period of stroke incidence in the region, to verify the law of stroke incidence and meteorological changes. Method: Use the stepwise regression method to screen out the most effective climatic factors. Use the circular distribution method to analyze the peak solar terms, calculate the angle of each solar term, and analyze the peak solar terms. Results: There was no absolute peak solar term for stroke onset, with Lichun and Jingzhe as the relative peaks. Combining this, the prevention of stroke in this kind of meteorology can be carried out clinically, which has very important guiding significance for the research on the prevention of related diseases by traditional Chinese medicine","PeriodicalId":315899,"journal":{"name":"Proceedings of the 1st International Symposium on Artificial Intelligence in Medical Sciences","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125581360","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Text classification of Diseases Treated by Traditional Chinese Medicine Prescription based on machine learning","authors":"Hanqing Zhao, Bo Han, Chen Li","doi":"10.1145/3429889.3429895","DOIUrl":"https://doi.org/10.1145/3429889.3429895","url":null,"abstract":"OBJECTIVE: To explore the application of machine learning in th e identification of diseases treated by traditional Chinese medicine prescriptions. METHODS: Based on the composition of the text document of Chinese medicine prescriptions, the prescriptions were divided into cough, headache and diarrhea. THUTCT were introduced to establish and train two machine learning text classification models, LibSVM and LibLinear, and the prescriptions to be deter mined were put into the model for classification and prediction. R ESULTS: The Precision rate of LibSVM model and Liblinear mod el were 0.7283 and 0.6690. Seven prescriptions were classified an d predicted, and the results were in line with expectations. CONCLUSION: THUCTC has good universality for the content of TCM prescriptions, high classification accuracy and fast testing speed, which is suitable for the text classification and discrimination research of TCM prescriptions for diseases.","PeriodicalId":315899,"journal":{"name":"Proceedings of the 1st International Symposium on Artificial Intelligence in Medical Sciences","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130261957","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Research on Traditional Chinese Medicine Data Mining Model Based on Traditional Chinese Medicine Basic Theories and Knowledge Graphs","authors":"Rui Xiao, Fengju Hu, Wei Pei, Minkun Bie","doi":"10.1145/3429889.3429909","DOIUrl":"https://doi.org/10.1145/3429889.3429909","url":null,"abstract":"In recent years, great progress has been made in the study of knowledge graph in various fields, and it has become a hot topic in Traditional Chinese Medicine (TCM) related fields. This paper utilizes a Chinese Herbal Medicine collection, which includes 537 medicines, retrieved from a hospital affiliated with a TCM university, as data source; referenced the Chinese Pharmacopoeia for building the knowledge graph founded on the basic TCM theory. Via associating the prescription with drug properties, taste and meridian tropism of Chinese medicine and visualizing the complex network of Chinese medicine prescription from a novel perspective, the rules in the prescription can be mined in a deeper level, which has a strong practical reference value for developing new clinical medicine and studying the prescription data mining.","PeriodicalId":315899,"journal":{"name":"Proceedings of the 1st International Symposium on Artificial Intelligence in Medical Sciences","volume":"186 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130544302","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluation of COVID-19 Epidemic Based on SIR Model","authors":"Leyao Wang","doi":"10.1145/3429889.3429893","DOIUrl":"https://doi.org/10.1145/3429889.3429893","url":null,"abstract":"Based on the SIR model, this article evaluates the efficiency of certain measures regarding new coronavirus (COVID-19). The data from the Provincial Health Committee and WHO are used to establish SIR model and draw graphs for evaluation. Simulations and pictures of SIR-F model are cited to predict the efficiency of certain measures. This article analyzes how the epidemic was regulated in different regions. The result shows that it is necessary to introduce strict regulations and take immediate actions so as to reduce the further spread of the virus.","PeriodicalId":315899,"journal":{"name":"Proceedings of the 1st International Symposium on Artificial Intelligence in Medical Sciences","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130546348","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Data Mining of the Effect of Cold and Heat Properties of Traditional Chinese Medicine on Normal Rats","authors":"Xiaoyuan Wang, Zheng-wei Gu, Shuai Feng","doi":"10.1145/3429889.3429931","DOIUrl":"https://doi.org/10.1145/3429889.3429931","url":null,"abstract":"Objective: To explore the hidden law of the mechanism of \"property and efficacy\" of traditional Chinese medicine (TCM) by using the changes of drug effect indexes caused by cold and hot herbs in normal rats. Methods: 4 / 5 samples of each group were randomly selected from all high-dose groups of traditional Chinese medicine as training set, and the remaining samples were composed of test set. Bayesian network was used to mine the experimental data of changes in drug effect indexes of normal rats caused by cold and hot traditional Chinese medicine. Results: the Bayesian network model of the relationship between cold and heat properties of traditional Chinese medicine and drug effect indexes of normal rats was obtained; conclusion: the validity and reliability of the network structure was verified by literature research, in the next step, we need to expand the sample size of traditional Chinese medicine and the range of selected indicators.","PeriodicalId":315899,"journal":{"name":"Proceedings of the 1st International Symposium on Artificial Intelligence in Medical Sciences","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124435357","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Heart Rate Variability Differences between Depression Patients with Different Severity and Healthy People","authors":"Jinhua Wang, Lulu Zhao, Baimin Li","doi":"10.1145/3429889.3429935","DOIUrl":"https://doi.org/10.1145/3429889.3429935","url":null,"abstract":"Depression is a normal mental disorder, whose levels were subjectively determined by psychiatrists, which lacks the support of physiological data. To aid clinical diagnosis, this study explored the relationship between the Heart Rate Variability (HRV) characteristics in healthy people and those of depression people with different severity. Thirty-six healthy volunteers, forty-six patients with moderate depression, and sixty-three patients with severe depression participated in the study. Their electrocardiogram signals were filtered to extract five heart rate variability characteristics, among which a new feature R-std was used to supplement the existing feature library. Statistical analysis was performed among the groups. The results showed that all the characteristics of depression patients significantly decreased compared with the healthy people, but the characteristic values did not decrease with the deepening of depression, and the new feature performed well. The five HRV indicators have significant differences between health and depression. The conclusion is that HRV indicators have significant differences between healthy and depressed mental states, and there are slight differences in the values of different depression degrees. Besides, the new features expand the indicators library. This study helps to better understand the relationship between HRV indexes and different mental states in clinical practice.","PeriodicalId":315899,"journal":{"name":"Proceedings of the 1st International Symposium on Artificial Intelligence in Medical Sciences","volume":"75 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131582075","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Limitation of on Big Data or Nature Language Processing based algorithm for Clinical Decision Artificial Intelligence","authors":"Ning Wu, Yanping Cao, Zhuo Chen, Yifan Zhu","doi":"10.1145/3429889.3429920","DOIUrl":"https://doi.org/10.1145/3429889.3429920","url":null,"abstract":"Intelligent clinical decision is an important utility of artificial intelligence. At present, most of its algorithm is based on big data or nature language processing. The limitation of such algorithm is discussed and summarized. That clinical decision artificial intelligence should meet the requirements of clinical medicine and artificial intelligence technique is proposed.","PeriodicalId":315899,"journal":{"name":"Proceedings of the 1st International Symposium on Artificial Intelligence in Medical Sciences","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132201944","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Artificial Intelligence in Medicine in the United States, China and India","authors":"Juan Chen, Yan Lu, Ting Zhang, Zhaolian Ouyang","doi":"10.1145/3429889.3429938","DOIUrl":"https://doi.org/10.1145/3429889.3429938","url":null,"abstract":"Objective: To compare the development status of artificial intelligence (AI) in medicine among the United States (US), China and India with bibliometric analysis. Methods: Articles involving AI in medicine published from 2015 to 2019 were retrieved on March 30, 2020 from Web of Science Core Collection. The country-level and the institution-level performance of the US, China and India in the field of AI in medicine were compared with indicators including the amount of papers, 5-year Compound Annual Growth Rate (CAGR) of the amount of papers, the amount of highly-cited papers, the proportion of highly-cited papers and the average citations per paper. In addition, the research hotspots and international cooperation of the three countries in recent 5 years were compared by conducting keywords co-occurrence analysis and co-authorship analysis in VOSviewer. Results: From 2015 to 2019, The US has published 7838 papers and 154 highly-cited papers in the field of AI in medicine, with an average citations per paper to be 9.3, and the proportion of highly-cited papers to be 2.0 %. China has output 6635 papers and 73 highly-cited papers in this field, with an average citations per paper to be 5.3, and the proportion of highly-cited papers to be 1.1%. India has output 3895 papers and 22 highly-cited papers in this field, with an average citations per paper to be 3.6, and the proportion of highly-cited papers to be 0.6%. The 5-year CAGR of the US, China and India in the period of 2015~2019 were 16.0%, 25.4% and 2.4%, respectively. At the institutional level, most of these indicators were significantly better for the US institutions than for Chinese and Indian ones. There were four research hotspots in this field, namely medical imaging technology, health big data mining, disease prediction with biomarkers and genetic information, and early diagnosis of neurological disease. The three countries focused on different hotspots, with China focusing relatively less on health big data mining, while the US and India being complementary to each other. As to international cooperation, the average links per paper to other countries were 0.60, 0.40 and 0.20, respectively, for the US, China and India. Conclusions: In the field of AI in medicine, the US, with a number of competitive institutions in AI and medical researches, is taking a definitely leading role, having conducted many innovative researches and cooperated extensively with other countries. China is taking the second leading role at the country level, with top institutions somewhat less productive than those in the US. India is the third productive country, with top institutions obvious less productive than those in the US, and with research hotspots exactly complementary to the US.","PeriodicalId":315899,"journal":{"name":"Proceedings of the 1st International Symposium on Artificial Intelligence in Medical Sciences","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132056880","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Speech-Driven 3-D Lip Synthesis with Realistic Dynamics in Mandarin Chinese","authors":"Changwei Liang, Xiaosheng Pan, Jiangping Kong","doi":"10.1145/3429889.3429904","DOIUrl":"https://doi.org/10.1145/3429889.3429904","url":null,"abstract":"In this paper, a new speech-driven lip synchronization method is developed, predicting the 3-D geometric shape of the lip without using speech recognition model in the visualization procedure, and can be trained and evaluated with realistic dynamics. Videos of Mandarin Chinese words are used. Speech signals are calculated into MFCC as audio features. 68-points facial landmarks are annotated from the corresponding videos through the prediction algorithm from the Dlib Library. Eos, a 3-D Morphable Face Model, is applied, using the facial landmarks, to predict the 3-D shape, where we can acquire 3-D landmarks. A machine-learning sequence-tagging model, averaged Structured Perceptron using Viterbi algorithm, is applied for modelling the direct prediction of labial parameters from the acoustic MFCC parameters. The 3-D labial area shape from the 'eos' prediction of a frame is morphed according to the predicted 3-D labial landmarks, forming the 3-D lip sequence, which can be plotted synchronically with the acoustic signal. In this 3-D lip synthesis, acoustic features and realistic lip shapes are directly mapped, where lip units and speech recognition are not applied, preserving more realistic articulatory or personality details; and the predicted geometric shapes are comparable with realistic dynamics, with the comparison indicating that this synthesis is of good effect.","PeriodicalId":315899,"journal":{"name":"Proceedings of the 1st International Symposium on Artificial Intelligence in Medical Sciences","volume":"104 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124184157","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Clinical Effect Analysis of Obstructive Sleep Apnea Hypopnea Syndrome","authors":"Yu Wang","doi":"10.1145/3429889.3429918","DOIUrl":"https://doi.org/10.1145/3429889.3429918","url":null,"abstract":"Objective: To compare the effect of combined nasal continuous positive airway pressure respiration combined with drugs on obstructive sleep apnea-hypopnea syndrome (OSAHS) in different conditions to further evaluate the clinical effect of OSAHS. 82 patients with OSAHS admitted to our hospital from January 2016 to December 2019 are selected and divided into 2 groups according to the severity of OSAHS disease. 52 patients with moderate OSAHS and 30 patients with severe OSAHS are treated with nasal-continuous positive airway pressure (CPAP) combined with pedomodorus and Monrothna. The sleep quality is evaluated before treatment and 3 months after treatment, and the average blood oxygen saturation at night and the longest hypopnea time is determined. Results show thatthe Pittsburgh sleep index score of patients in the severe OSAHS group before treatment is lower than that in the moderate OSAHS group, and the average blood oxygen saturation level at night is higher than that in the moderate OSAHS group. The longest hypoventilation time is shorter than that in the OSAHS group. The difference is statistically significant (P <0.05); after 3 months of treatment, this index is improved in both groups, and Pittsburgh sleep index score, mean nighttime blood oxygen saturation level and time difference of longest hypoventilation are significantly higher in the moderate OSAHS group before and after 3 months of treatment than in the severe OSAHS group, with statistically significant differences (P<0.05). Therefore, the treatment of OSAHS patients with CPAPcombined with Peidomod and Monrothna can effectively improve the sleep quality, increase the mean oxygen saturation at night, and reduce the duration of hypoventilation. However, it should be implemented as soon as possible to improve the clinical effect.","PeriodicalId":315899,"journal":{"name":"Proceedings of the 1st International Symposium on Artificial Intelligence in Medical Sciences","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114912499","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}