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Original Article

A Machine Learning Framework for Automatic and Continuous MMN Detection with Preliminary Results for Coma Outcome Prediction

Hari Chandana1 Amogha P2 Bhumika S3 Chandana KN4 Chithra PK5
1 Professor, Guide, Department of Computer Science and Engineering, Rajarajeswari College of Engineering, Bangalore, Karnataka, India. 2 3 4 5 Department of Computer Science and Engineering, Rajarajeswari College of Engineering, Bangalore, Karnataka, India.

Published Online: November-December 2025

Pages: 105-112

References

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3. H. L. Lew, J. H. Poole, A. Castaneda, R. M. Salerno, and M. Gray, “Prognostic value of evoked and event-related potentials in moderate to severe brain injury,” Journal of Head Trauma Rehabilitation, vol. 21, no. 4, pp. 350–360, 2006.
4. C. C. Duncan et al., “Event-related potentials in clinical research: Guidelines for eliciting, recording, and quantifying mismatch negativity, P300, and N400,” Clinical Neurophysiology, vol.120, no. 11, pp. 1883–1908, 2009.
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8. M. Macdonald, P. Jamshidi, and K. Campbell, “Infrequent increases in stimulus intensity may interrupt central executive functioning during REM sleep,” NeuroReport, vol. 19, no. 3, pp.309–313, 2008.
9. L. D. Sculthorpe, D. R. Ouellet, and K. B.Campbell, “MMN elicitation during natural sleep to violations of an auditory pattern,” Brain Research, vol. 1290, pp. 52–62, 2009.
10. M. Strauss et al., “Disruption of hierarchical predictive coding during sleep,” Proceedings of the National Academy of Sciences, vol. 112, no.11pp. E1353–E1362, 2015.
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