PREDICTING THE DEPTH OF ANESTHESIA FOR OPERATING PATIENT USING MUSIC-BASED SPECTRAL FEATURES OF EEG SIGNALS /
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| Format: | Bog |
| Sprog: | engelsk |
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Dhaka :
BME DEPT. MIST,
c2023.
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Lignende værker: PREDICTING THE DEPTH OF ANESTHESIA FOR OPERATING PATIENT USING MUSIC-BASED SPECTRAL FEATURES OF EEG SIGNALS /
- PREDICTING THE DEPTH OF ANESTHESIA FOR OPERATING PATIENT USING MUSIC-BASED SPECTRAL FEATURES OF EEG SIGNALS
- CLASSIFICATION PERFORMANCE EVALUATION OF DIFFERENT RHYTHMIC BANDS OF EEG BASED ANESTHESIA MONITORING /
- ATTEMPTED MOVEMENT CLASSIFICATION OF SPINAL CORD INJURED PATIENTS COMBINING CNN AND LSTM NETWORK /
- MACHINE LEARNING BASED SEPSIS PREDICTION FOR FOOT INFECTION IN DIABETIC PATIENTS /
- AFFECTIVE STATE RECOGNITION THROUGH EEG SIGNALS FEATURE LEVEL FUSION AND ENSEMBLE CLASSIFIER /
- DEVELOPMENT AND ASSESSMENT OF CARBOXYMETHYL CELLULOSE LOADED ZINC OXIDE NANOPARTICLES FOR ANTIBACTERIAL PROPERTIES /