Computer Science ›› 2017, Vol. 44 ›› Issue (Z11): 29-32.doi: 10.11896/j.issn.1002-137X.2017.11A.005

Previous Articles     Next Articles

Application Survey of Artificial Intelligence in Neurology

LI Shi-yu, WANG Feng, CAO Bin and MEI Qi   

  • Online:2018-12-01 Published:2018-12-01

Abstract: Artificial intelligence affects all aspects of people’s lives,and medical treatment has become one of the most popular areas of artificial intelligence.More and more artificial intelligence equipments are used to assist doctors in the diagnosis and treatment.The application of artificial intelligence in neurology was reviewed,especially for the diagnosis of Parkinson’s disease and Alzheimer’s disease.Firstly,the development history,classification and application status of artificial intelligence were expounded.Secondly,the research status of artificial intelligence diagnosis of Parkinson’s di-sease and Alzheimer’s disease was summarized,and the key technologies used to diagnosis Parkinson’s disease and Alzheimer’s disease were analyzed.Finally,The technology in the application of medicine was summarized,and the importance of the application of artificial intelligence in the medical field was clarified.The future research direction of artificial intelligence in the application of neurology was prospected.

Key words: Artificial intelligence,Parkinson,Alzheimer’s disease

[1] 余凯,等.深度学习的昨天、今天和明天[J].计算机研究与发展,2013(9):1799-1804.
[2] 尹宝才,王文通,王立春.深度学习研究综述[J].北京工业大学学报,2015(1):48-59.
[3] 刘建伟,刘媛,罗雄麟.深度学习研究进展[J].计算机应用研究,2014,31(7):1921-1930.
[4] ESTEVA A,KUPREL B,NOVOA R A,et al.Dermatologist-level classification of skin cancer with deep neural networks[J].Nature,2017,542(7639):115.
[5] 韩晔彤.人工智能技术发展及应用研究综述[J].电子制作,2016(12):95-95.
[6] SHETTY S,RAO Y S.SVM Based Machine Learning Approach to Identify Parkinson’s Disease Using Gait Analysis[C]∥International Conference on Inventive Computation Technologies (ICICT).2016.
[7] FRID A,KANTOR A,SVECHIN D,et al.Diagnosis of Parkinson’s Disease from Continuous Speech using Deep Convolutional Networks without Manual Selection of Features[C]∥International Conference on the Science of Electrical Engineering.2016.
[8] 丁宏娟,何建成,周阿高.帕金森病早期诊断的中西结合方法探索[C]∥中国中西医结合学会诊断专业委员会2009’年会论文集.2009.
[9] LI Z,ZHANG Y.Application of arithmetic CAP2 in medical diagnosis expert system[C]∥International Conference on Education Technology and Computer.IEEE,2010:V2-297-V2-299.
[10] PEREIRA C R,WEBER S A T,HOOK C,et al.Deep Learning-Aided Parkinson’s Disease Diagnosis from Handwritten Dyna-mics[C]∥SIBGRAPI 2016-Conference on Graphics,Patterns and Images.2016:340-346.
[11] FUKAWA K,OKUNO R,YOKOE M,et al.Estimation of UPDRS Finger Tapping Score by using Artificial Neural Network for Quantitative Diagnosis of Parkinson’s disease[C]∥International Special Topic Conference on Information Technology Applications in Biomedicine.Tokyo:IEEE,2007:259-260.
[12] CABESTANY J,LPEZ C P,SAMA A,et al.REMPARK: When AI and technology meet Parkinson Disease assessment[M]∥Mixed Design of Integrated Circuits and Systems.IEEE,2013:562-567.
[13] KUBOTA K J,CHEN J A,LITTLE M A.Machine learning for large-scale wearable sensor data in Parkinson’s disease:Concepts,promises,pitfalls,and futures[J].Movement Disorders Official Journal of the Movement Disorder Society,2016,31(9):1314.
[14] AGARWAL A,CHANDRAYAN S,SAHU S S.Prediction of Parkinson’s Disease using Speech Signal with Extreme Learning Machine[C]∥2016 International Conference on Electrical,Electronics,and Optimization Techniques (ICEEOT).2016:3776-3779.
[15] BLAHUTA J,SOUKUP T,CERMAK P,et al.Ultrasound medi-cal image recognition with artificial intelligence for Parkinson’s disease classification[C]∥2012 Proceedings of the International Convention.2012:958-962.
[16] BHATKOTI P,PAUL M.Early diagnosis of Alzheimer’s di-sease:A multi-class deep learning framework with modified k-sparse autoencoder classification[C]∥IEEE Image and Vision Computing.New Zealand,IEEE,2017.
[17] 张勇,刘小莉,郭利锋.SPECT/CT影像技术用于阿尔兹海默症患者诊断的临床价值分析[J].中国民康医学,2017,29(2):4-5.
[18] UEMURA T,ISHII K,MIYAMOTO N,et al.Computer-assisted system for diagnosis of Alzheimer disease using data base- independent estimation and fluorodeoxyglucose-positron-emission tomography and 3D-stereotactic surface projection[J].Ajnr American Journal of Neuroradiology,2011,32(3):556-559.
[19] TRIPOLITI E E,FOTIADIS D I,ARGYROPOULOU M.A supervised method to assist the diagnosis and classification of the status of Alzheimer’s disease using data from an fMRI experiment[C]∥ 30th Annual International IEEE EMBS Conference.2008:20-24.
[20] SARRAF S,TOFIGHI G.Deep learning-based pipeline to recognize Alzheimer’s disease using fMRI data[C]∥Future Technolo-gies Conference.2016.
[21] GAO X W,HUI R.A deep learning based approach to classification of CT brain images[C]∥Sai Computing Conference.2016:28-31.
[22] MORABITO F C,CAMPOLO M,IERACITANO C,et al.Deep convolutional neural networks for classification of mild cognitive impaired and Alzheimer’s disease patients from scalp EEG recordings[C]∥International Forum on Research and Technologies for Society and Industry Leveraging A Better Tomorrow.IEEE,2016:1-6.
[23] JOSHI S,SHENOY D,VIBHUDENDRA S G G,et al.Classification of Alzheimer’s Disease and Parkinson’s Disease by Using Machine Learning and Neural Network Methods[M].IEEE Computer Society,2010.
[24] HOSSEINI-ASL E,KEYNTON R,EL-BAZ A.Alzheimer’sdisease diagnostics by adaptation of 3D convolutional network[C]∥IEEE International Conference on Image Processing.IEEE,2016.

No related articles found!
Full text



No Suggested Reading articles found!