Harvard Catalyst Profiles

Contact, publication, and social network information about Harvard faculty and fellows.

Sydney S. Cash, M.D.,Ph.D.

Co-Author

This page shows the publications co-authored by Sydney Cash and Michael Westover.
Connection Strength

8.511
  1. The probability of seizures during EEG monitoring in critically ill adults. Clin Neurophysiol. 2015 Mar; 126(3):463-71.
    View in: PubMed
    Score: 0.604
  2. Inferring seizure frequency from brief EEG recordings. J Clin Neurophysiol. 2013 Apr; 30(2):174-7.
    View in: PubMed
    Score: 0.553
  3. Revising the "Rule of Three" for inferring seizure freedom. Epilepsia. 2012 Feb; 53(2):368-76.
    View in: PubMed
    Score: 0.506
  4. Responsive neurostimulation for focal motor status epilepticus. Ann Clin Transl Neurol. 2021 06; 8(6):1353-1361.
    View in: PubMed
    Score: 0.242
  5. Night-to-night variability of sleep electroencephalography-based brain age measurements. Clin Neurophysiol. 2021 01; 132(1):1-12.
    View in: PubMed
    Score: 0.234
  6. Association of epileptiform abnormalities and seizures in Alzheimer disease. Neurology. 2020 10 20; 95(16):e2259-e2270.
    View in: PubMed
    Score: 0.230
  7. Cost-effectiveness analysis of multimodal prognostication in cardiac arrest with EEG monitoring. Neurology. 2020 08 04; 95(5):e563-e575.
    View in: PubMed
    Score: 0.229
  8. Reactivation of Motor-Related Gamma Activity in Human NREM Sleep. Front Neurosci. 2020; 14:449.
    View in: PubMed
    Score: 0.226
  9. Development of Expert-Level Automated Detection of Epileptiform Discharges During Electroencephalogram Interpretation. JAMA Neurol. 2020 01 01; 77(1):103-108.
    View in: PubMed
    Score: 0.221
  10. Interrater Reliability of Experts in Identifying Interictal Epileptiform Discharges in Electroencephalograms. JAMA Neurol. 2020 01 01; 77(1):49-57.
    View in: PubMed
    Score: 0.221
  11. Quantitative EEG reactivity and machine learning for prognostication in hypoxic-ischemic brain injury. Clin Neurophysiol. 2019 10; 130(10):1908-1916.
    View in: PubMed
    Score: 0.214
  12. A fast machine learning approach to facilitate the detection of interictal epileptiform discharges in the scalp electroencephalogram. J Neurosci Methods. 2019 10 01; 326:108362.
    View in: PubMed
    Score: 0.214
  13. Estimating the False Positive Rate of Absent Somatosensory Evoked Potentials in Cardiac Arrest Prognostication. Crit Care Med. 2018 12; 46(12):e1213-e1221.
    View in: PubMed
    Score: 0.205
  14. EEG Reactivity Evaluation Practices for Adult and Pediatric Hypoxic-Ischemic Coma Prognostication in North America. J Clin Neurophysiol. 2018 Nov; 35(6):510-514.
    View in: PubMed
    Score: 0.204
  15. Brain age from the electroencephalogram of sleep. Neurobiol Aging. 2019 02; 74:112-120.
    View in: PubMed
    Score: 0.203
  16. CLASSIFIER CASCADE TO AID IN DETECTION OF EPILEPTIFORM TRANSIENTS IN INTERICTAL EEG. Proc IEEE Int Conf Acoust Speech Signal Process. 2018 Apr; 2018:970-974.
    View in: PubMed
    Score: 0.202
  17. Antiepileptic drug treatment after an unprovoked first seizure: A decision analysis. Neurology. 2018 10 09; 91(15):e1429-e1439.
    View in: PubMed
    Score: 0.202
  18. A Mean Field Model of Acute Hepatic Encephalopathy. Annu Int Conf IEEE Eng Med Biol Soc. 2018 Jul; 2018:2366-2369.
    View in: PubMed
    Score: 0.199
  19. EEG CLassification Via Convolutional Neural Network-Based Interictal Epileptiform Event Detection. Annu Int Conf IEEE Eng Med Biol Soc. 2018 Jul; 2018:3148-3151.
    View in: PubMed
    Score: 0.199
  20. Continuous electroencephalography predicts delayed cerebral ischemia after subarachnoid hemorrhage: A prospective study of diagnostic accuracy. Ann Neurol. 2018 05; 83(5):958-969.
    View in: PubMed
    Score: 0.197
  21. Epileptiform activity in traumatic brain injury predicts post-traumatic epilepsy. Ann Neurol. 2018 04; 83(4):858-862.
    View in: PubMed
    Score: 0.196
  22. Automated epileptiform spike detection via affinity propagation-based template matching. Annu Int Conf IEEE Eng Med Biol Soc. 2017 Jul; 2017:3057-3060.
    View in: PubMed
    Score: 0.186
  23. Epileptiform abnormalities predict delayed cerebral ischemia in subarachnoid hemorrhage. Clin Neurophysiol. 2017 06; 128(6):1091-1099.
    View in: PubMed
    Score: 0.180
  24. FAST AND EFFICIENT REJECTION OF BACKGROUND WAVEFORMS IN INTERICTAL EEG. Proc IEEE Int Conf Acoust Speech Signal Process. 2016 Mar; 2016:744-748.
    View in: PubMed
    Score: 0.172
  25. CLUSTERING OF INTERICTAL SPIKES BY DYNAMIC TIME WARPING AND AFFINITY PROPAGATION. Proc IEEE Int Conf Acoust Speech Signal Process. 2016 Mar; 2016:749-753.
    View in: PubMed
    Score: 0.172
  26. EPILEPTIFORM SPIKE DETECTION VIA CONVOLUTIONAL NEURAL NETWORKS. Proc IEEE Int Conf Acoust Speech Signal Process. 2016 Mar; 2016:754-758.
    View in: PubMed
    Score: 0.172
  27. Rapid annotation of interictal epileptiform discharges via template matching under Dynamic Time Warping. J Neurosci Methods. 2016 12 01; 274:179-190.
    View in: PubMed
    Score: 0.169
  28. The number of seizures needed in the EMU. Epilepsia. 2015 Nov; 56(11):1753-9.
    View in: PubMed
    Score: 0.162
  29. The human burst suppression electroencephalogram of deep hypothermia. Clin Neurophysiol. 2015 Oct; 126(10):1901-1914.
    View in: PubMed
    Score: 0.157
  30. The standardization debate: A conflation trap in critical care electroencephalography. Seizure. 2015 Jan; 24:52-8.
    View in: PubMed
    Score: 0.154
  31. Weighing the value of memory loss in the surgical evaluation of left temporal lobe epilepsy: a decision analysis. Epilepsia. 2014 Nov; 55(11):1844-53.
    View in: PubMed
    Score: 0.153
  32. Spectrogram screening of adult EEGs is sensitive and efficient. Neurology. 2014 Jul 01; 83(1):56-64.
    View in: PubMed
    Score: 0.150
  33. SpikeGUI: software for rapid interictal discharge annotation via template matching and online machine learning. Annu Int Conf IEEE Eng Med Biol Soc. 2014; 2014:4435-8.
    View in: PubMed
    Score: 0.146
  34. Calculating the risk benefit equation for aggressive treatment of non-convulsive status epilepticus. Neurocrit Care. 2013 Apr; 18(2):216-27.
    View in: PubMed
    Score: 0.138
  35. Real-time segmentation and tracking of brain metabolic state in ICU EEG recordings of burst suppression. Annu Int Conf IEEE Eng Med Biol Soc. 2013; 2013:7108-11.
    View in: PubMed
    Score: 0.136
  36. Information theoretic quantification of diagnostic uncertainty. Open Med Inform J. 2012; 6:36-50.
    View in: PubMed
    Score: 0.135
  37. Absence of early epileptiform abnormalities predicts lack of seizures on continuous EEG. Neurology. 2012 Oct 23; 79(17):1796-801.
    View in: PubMed
    Score: 0.134
  38. Emergence of stable functional networks in long-term human electroencephalography. J Neurosci. 2012 Feb 22; 32(8):2703-13.
    View in: PubMed
    Score: 0.128
  39. Real-time segmentation of burst suppression patterns in critical care EEG monitoring. J Neurosci Methods. 2013 Sep 30; 219(1):131-41.
    View in: PubMed
    Score: 0.071
  40. Expert-level automated sleep staging of long-term scalp electroencephalography recordings using deep learning. Sleep. 2020 11 12; 43(11).
    View in: PubMed
    Score: 0.059
  41. Electrographic predictors of successful weaning from anaesthetics in refractory status epilepticus. Brain. 2020 04 01; 143(4):1143-1157.
    View in: PubMed
    Score: 0.056
  42. Detection of mesial temporal lobe epileptiform discharges on intracranial electrodes using deep learning. Clin Neurophysiol. 2020 01; 131(1):133-141.
    View in: PubMed
    Score: 0.055
  43. Quantitative Electroencephalogram Trends Predict Recovery in Hypoxic-Ischemic Encephalopathy. Crit Care Med. 2019 10; 47(10):1416-1423.
    View in: PubMed
    Score: 0.054
  44. Reply: Computer models to inform epilepsy surgery strategies: prediction of postoperative outcome. Brain. 2017 05 01; 140(5):e31.
    View in: PubMed
    Score: 0.046
  45. A disk-aware algorithm for time series motif discovery. Data Min Knowl Discov. 2011 Jan; 22(1-2):73-105.
    View in: PubMed
    Score: 0.028
Connection Strength
The connection strength for co-authors is the sum of the scores for each of their shared publications.

Publication scores are based on many factors, including how long ago they were written and whether the person is a first or senior author.
Funded by the NIH National Center for Advancing Translational Sciences through its Clinical and Translational Science Awards Program, grant number UL1TR002541.