347 related articles for article (PubMed ID: 29785154)
21. Major depressive disorder assessment via enhanced k-nearest neighbor method and EEG signals.
Saeedi M; Saeedi A; Maghsoudi A
Phys Eng Sci Med; 2020 Sep; 43(3):1007-1018. PubMed ID: 32662038
[TBL] [Abstract][Full Text] [Related]
22. Machine learning based congestive heart failure detection using feature importance ranking of multimodal features.
Hussain L; Aziz W; Khan IR; Alkinani MH; Alowibdi JS
Math Biosci Eng; 2020 Nov; 18(1):69-91. PubMed ID: 33525081
[TBL] [Abstract][Full Text] [Related]
23. A Novel Extreme Learning Machine Classification Model for e-Nose Application Based on the Multiple Kernel Approach.
Jian Y; Huang D; Yan J; Lu K; Huang Y; Wen T; Zeng T; Zhong S; Xie Q
Sensors (Basel); 2017 Jun; 17(6):. PubMed ID: 28629202
[TBL] [Abstract][Full Text] [Related]
24. Direct Kernel Perceptron (DKP): ultra-fast kernel ELM-based classification with non-iterative closed-form weight calculation.
Fernández-Delgado M; Cernadas E; Barro S; Ribeiro J; Neves J
Neural Netw; 2014 Feb; 50():60-71. PubMed ID: 24287336
[TBL] [Abstract][Full Text] [Related]
25. Extreme Learning Machine for Heartbeat Classification with Hybrid Time-Domain and Wavelet Time-Frequency Features.
Xu Y; Zhang S; Cao Z; Chen Q; Xiao W
J Healthc Eng; 2021; 2021():6674695. PubMed ID: 33505643
[TBL] [Abstract][Full Text] [Related]
26. Hierarchical multi-class SVM with ELM kernel for epileptic EEG signal classification.
Murugavel AS; Ramakrishnan S
Med Biol Eng Comput; 2016 Jan; 54(1):149-61. PubMed ID: 26296799
[TBL] [Abstract][Full Text] [Related]
27. A Novel Fault Diagnosis Method for Rolling Bearing Based on Hierarchical Refined Composite Multiscale Fluctuation-Based Dispersion Entropy and PSO-ELM.
Chen Y; Yuan Z; Chen J; Sun K
Entropy (Basel); 2022 Oct; 24(11):. PubMed ID: 36359611
[TBL] [Abstract][Full Text] [Related]
28. An approach to predict Sudden Cardiac Death (SCD) using time domain and bispectrum features from HRV signal.
Houshyarifar V; Chehel Amirani M
Biomed Mater Eng; 2016 Aug; 27(2-3):275-85. PubMed ID: 27567781
[TBL] [Abstract][Full Text] [Related]
29. Emotional State Recognition from Peripheral Physiological Signals Using Fused Nonlinear Features and Team-Collaboration Identification Strategy.
Pan L; Yin Z; She S; Song A
Entropy (Basel); 2020 Apr; 22(5):. PubMed ID: 33286283
[TBL] [Abstract][Full Text] [Related]
30. Detection of Coronary Artery Disease Using Multi-Domain Feature Fusion of Multi-Channel Heart Sound Signals.
Liu T; Li P; Liu Y; Zhang H; Li Y; Jiao Y; Liu C; Karmakar C; Liang X; Ren M; Wang X
Entropy (Basel); 2021 May; 23(6):. PubMed ID: 34064025
[TBL] [Abstract][Full Text] [Related]
31. Automated detection of sleep apnea using sparse residual entropy features with various dictionaries extracted from heart rate and EDR signals.
Viswabhargav CSS; Tripathy RK; Acharya UR
Comput Biol Med; 2019 May; 108():20-30. PubMed ID: 31003176
[TBL] [Abstract][Full Text] [Related]
32. Pathological brain detection in MRI scanning by wavelet packet Tsallis entropy and fuzzy support vector machine.
Zhang YD; Wang SH; Yang XJ; Dong ZC; Liu G; Phillips P; Yuan TF
Springerplus; 2015; 4(1):716. PubMed ID: 26636004
[TBL] [Abstract][Full Text] [Related]
33. Classification of Emotional States Using EEG Signals and Wavelet Packet Transform Features.
Kumar H; Ganapathy N; Puthankattil SD; Swaminathan R
Stud Health Technol Inform; 2022 May; 294():943-944. PubMed ID: 35612250
[TBL] [Abstract][Full Text] [Related]
34. Prediction and early detection of delirium in the intensive care unit by using heart rate variability and machine learning.
Oh J; Cho D; Park J; Na SH; Kim J; Heo J; Shin CS; Kim JJ; Park JY; Lee B
Physiol Meas; 2018 Mar; 39(3):035004. PubMed ID: 29376502
[TBL] [Abstract][Full Text] [Related]
35. Comparing Different Methods of Hand-crafted HRV, EDR and CPC Features for Sleep Apnoea Detection.
Sadr N; Chazal P
Annu Int Conf IEEE Eng Med Biol Soc; 2019 Jul; 2019():3870-3873. PubMed ID: 31946718
[TBL] [Abstract][Full Text] [Related]
36. Automated FBSE-EWT based learning framework for detection of epileptic seizures using time-segmented EEG signals.
Anuragi A; Sisodia DS; Pachori RB
Comput Biol Med; 2021 Sep; 136():104708. PubMed ID: 34358996
[TBL] [Abstract][Full Text] [Related]
37. [Drug discrimination by near infrared spectroscopy based on summation wavelet extreme learning machine].
Liu ZB; Jiang SJ; Yang HH; Zhang XB
Guang Pu Xue Yu Guang Pu Fen Xi; 2014 Oct; 34(10):2815-20. PubMed ID: 25739231
[TBL] [Abstract][Full Text] [Related]
38. Detection of Parkinson's disease from EEG signals using discrete wavelet transform, different entropy measures, and machine learning techniques.
Aljalal M; Aldosari SA; Molinas M; AlSharabi K; Alturki FA
Sci Rep; 2022 Dec; 12(1):22547. PubMed ID: 36581646
[TBL] [Abstract][Full Text] [Related]
39. Gaussian process-based kernel as a diagnostic model for prediction of type 2 diabetes mellitus risk using non-linear heart rate variability features.
Shashikant R; Chaskar U; Phadke L; Patil C
Biomed Eng Lett; 2021 Aug; 11(3):273-286. PubMed ID: 34350053
[TBL] [Abstract][Full Text] [Related]
40. Detection of Stress Levels from Biosignals Measured in Virtual Reality Environments Using a Kernel-Based Extreme Learning Machine.
Cho D; Ham J; Oh J; Park J; Kim S; Lee NK; Lee B
Sensors (Basel); 2017 Oct; 17(10):. PubMed ID: 29064457
[TBL] [Abstract][Full Text] [Related]
[Previous] [Next] [New Search]
