Support vector machines - Globe Thesis

Keyword [Support vector machines] Result: 21 - 40 \| Page: 2 of 5
21.	Research And Application Of Support Vector Machine Technology In Computer-aided Medical Diagnosing System For Breast Cancer
22.	Application Of Serum Protein Fingerprint Model In Diagnosis Of Renal Cell Carcinoma And Their Clinical Significance
23.	A Brain Shift Correction Model Based On The Fuzzy Support Vector Machines (fsvm) With Different Constant Term
24.	Machine Learning Methods Applied Research In The Brain - Machine Interface Technology
25.	Commonly Used In Herbal Medicine Near Infrared Spectroscopy Database And Identify The Research
26.	Comparison Of Classification Methods For Property Of Chinese Medicinal Herbs Based On Original Characters
27.	Feature Extraction And Analysis Of Emotional Pictures Visual Evoked EEG
28.	Study On The Prediction Of Intracranial Hypertension Based On Waveform Feature Extraction And Support Vector Machines Classification
29.	Renal Artery Doppler Ultrasound Diagnosis Research
30.	Mirna Structure And Cancer Related Research Based On Computational Methods
31.	Brain Network Characteristics In Brain Tumor Patients Revealed By Functional Network Analysis Based On FMRI Dataset
32.	The Application Of Multi-modal Functional MRI Technology In The Diagnosis And Classification Of Clinical Phenotypes Of Parkinsonâ€™s Disease
33.	The Research On Sleepiness Detection Based On ECG And Pulse Signals
34.	Quality Testing Of Chinese Medicinal Materials Based On Machine Olfaction
35.	Study On The Model Of Discriminating Head Injury Severity
36.	Simulation Analysis And Recognition Of Pulse Signal Based On The Electricity Network Of Cardiovascular
37.	Epileptic Eeg Signal Classification Based On Wavelet Packet Transform And Multivariate Multiscale Entropy
38.	Research Of Motor Imagery Recognition And Proprioceptive Feedback On EEG Controlled Prosthesis
39.	Using R To Fit A Hybrid ARIMA And Support Vector Machines Model In Tuberculosis Incidence Forecasting Of Jiangxi Province
40.	An Ovarian Cancer Detection Model Based On Probabilistic Principal Components Analysis And Support Vector Machine
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