Computerized application for epilepsy in China: Does the era of artificial intelligence comes?

被引:3
作者
Gong, Yiwei [1 ]
Xu, Cenglin [1 ]
Wang, Shuang [2 ]
Wang, Yi [1 ]
Chen, Zhong [1 ]
机构
[1] Zhejiang Chinese Med Univ, Sch Pharmaceut Sci, Key Lab Neuropharmacol & Translat Med Zhejiang Pr, Hangzhou, Peoples R China
[2] Zhejiang Univ, Affiliated Hosp 2, Epilepsy Ctr, Sch Med, Hangzhou, Peoples R China
来源
ACTA NEUROLOGICA SCANDINAVICA | 2022年 / 146卷 / 06期
基金
中国国家自然科学基金;
关键词
artificial intelligence; computation science; epilepsy; precise medicine; INTERICTAL EPILEPTIFORM DISCHARGES; HIGH-FREQUENCY OSCILLATIONS; SEIZURE PREDICTION; EEG SPIKE; LOCALIZATION; CLASSIFICATION; SYNCHRONIZATION; DIAGNOSIS; DISORDER; NETWORKS;
D O I
10.1111/ane.13711
中图分类号
R74 [神经病学与精神病学];
学科分类号
摘要
Epilepsy, one of the most common neurological diseases in China, is notorious for its spontaneous, unprovoked and recurrent seizures. The etiology of epilepsy varies among individual patients, including congenital gene mutation, traumatic injury, infections, etc. This heterogeneity partly hampered the accurate diagnosis and choice of appropriate treatments. Encouragingly, great achievements have been achieved in computational science, making it become a key player in medical fields gradually and bringing new hope for rapid and accurate diagnosis as well as targeted therapies in epilepsy. Here, we historically review the advances of computerized applications in epilepsy-especially those tremendous findings achieved in China-for different purposes including seizure prediction, localization of epileptogenic zone, post-surgical prognosis, etc. Special attentions are paid to the great progress based on artificial intelligence (AI), which is more "sensitive", "smart" and "in-depth" than human capacities. At last, we give a comprehensive discussion about the disadvantages and limitations of current computerized applications for epilepsy and propose some future directions as further stepping stones to embrace "the era of AI" in epilepsy.
引用
收藏
页码:732 / 742
页数:11
相关论文
共 104 条
[21]   CONTEXT-BASED AUTOMATED DETECTION OF EPILEPTOGENIC SHARP TRANSIENTS IN THE EEG - ELIMINATION OF FALSE POSITIVES [J].
GLOVER, JR ;
RAGHAVAN, N ;
KTONAS, PY ;
FROST, JD .
IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, 1989, 36 (05) :519-527
[22]   Computer-aided navigation in neurosurgery [J].
P. Grunert ;
K. Darabi ;
J. Espinosa ;
R. Filippi .
Neurosurgical Review, 2003, 26 (2) :73-99
[23]   Maximally selective single-cell target for circuit control in epilepsy models [J].
Hadjiabadi, Darian ;
Lovett-Barron, Matthew ;
Raikov, Ivan Georgiev ;
Sparks, Fraser T. ;
Liao, Zhenrui ;
Baraban, Scott C. ;
Leskovec, Jure ;
Losonczy, Attila ;
Deisseroth, Karl ;
Soltesz, Ivan .
NEURON, 2021, 109 (16) :2556-+
[24]   Identifying Epilepsy Based on Deep Learning Using DKI Images [J].
Huang, Jianjun ;
Xu, Jiahui ;
Kang, Li ;
Zhang, Tijiang .
FRONTIERS IN HUMAN NEUROSCIENCE, 2020, 14
[25]   Early Prediction of Refractory Epilepsy in Children Under Artificial Intelligence Neural Network [J].
Huang, Yueyan ;
Li, Qingfeng ;
Yang, Qian ;
Huang, Zhijing ;
Gao, Hongbo ;
Xu, Yunan ;
Liao, Lianghua .
FRONTIERS IN NEUROROBOTICS, 2021, 15
[26]  
Huang Z C, 1993, Zhonghua Nei Ke Za Zhi, V32, P831
[27]   Studies on quantitative beta activity in EEG background changes produced by intravenous diazepam in epilepsy [J].
Huang, ZC ;
Shen, DL .
CLINICAL ELECTROENCEPHALOGRAPHY, 1997, 28 (03) :172-178
[28]   THE PROGNOSTIC-SIGNIFICANCE OF DIAZEPAM-INDUCED EEG CHANGES IN EPILEPSY - A FOLLOW-UP-STUDY [J].
HUANG, ZC ;
SHEN, DL .
CLINICAL ELECTROENCEPHALOGRAPHY, 1993, 24 (04) :179-187
[29]   Brain beta-amyloid measures and magnetic resonance imaging atrophy both predict time-to-progression from mild cognitive impairment to Alzheimer's disease [J].
Jack, Clifford R., Jr. ;
Wiste, Heather J. ;
Vemuri, Prashanthi ;
Weigand, Stephen D. ;
Senjem, Matthew L. ;
Zeng, Guang ;
Bernstein, Matt A. ;
Gunter, Jeffrey L. ;
Pankratz, Vernon S. ;
Aisen, Paul S. ;
Weiner, Michael W. ;
Petersen, Ronald C. ;
Shaw, Leslie M. ;
Trojanowski, John Q. ;
Knopman, David S. .
BRAIN, 2010, 133 :3336-3348
[30]   Detection of Interictal Epileptiform Discharges Using Signal Envelope Distribution Modelling: Application to Epileptic and Non-Epileptic Intracranial Recordings [J].
Janca, Radek ;
Jezdik, Petr ;
Cmejla, Roman ;
Tomasek, Martin ;
Worrell, Gregory A. ;
Stead, Matt ;
Wagenaar, Joost ;
Jefferys, John G. R. ;
Krsek, Pavel ;
Komarek, Vladimir ;
Jiruska, Premysl ;
Marusic, Petr .
BRAIN TOPOGRAPHY, 2015, 28 (01) :172-183