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1. Classification of Epileptic and Psychogenic Non-Epileptic Seizures Using Electroencephalography and Electrocardiography

2. Forecasting seizure likelihood from cycles of self-reported events and heart rate: a prospective pilot studyResearch in context

3. Ambulatory seizure forecasting with a wrist-worn device using long-short term memory deep learning

4. Multiday cycles of heart rate are associated with seizure likelihood: An observational cohort study

5. Seizure Forecasting Using a Novel Sub-Scalp Ultra-Long Term EEG Monitoring System

6. Epileptic Seizure Cycles: Six Common Clinical Misconceptions

7. Seizure Diaries and Forecasting With Wearables: Epilepsy Monitoring Outside the Clinic

15. Deep Learning for Automated Detection of Generalized Paroxysmal Fast Activity in Lennox-Gastaut Syndrome

18. Ambulatory Video EEG extended to 10 days: A retrospective review of a large database of ictal events

19. Rates of Event Capture of Ambulatory Video EEG

20. Multimodal wearable sensors inform cycles of seizure risk

21. Seizure forecasting using minimally invasive, ultra‐long‐term subcutaneous EEG: Generalizable cross‐patient models

22. Cycles of self‐reported seizure likelihood correspond to yield of diagnostic epilepsy monitoring

23. 230 days of ultra long‐term subcutaneous EEG: seizure cycle analysis and comparison to patient diary

24. Forecasting cycles of seizure likelihood

25. Seizure forecasting using minimally invasive, ultra‐long‐term subcutaneous electroencephalography: Individualized intrapatient models

26. Ambient air pollution and epileptic seizures: A panel study in Australia

27. Water-soluble adhesive for stable long-term ambulatory EEG recordings

28. Seizure forecasting: bifurcations in the long and winding road

29. Ambulatory seizure forecasting with a wrist-worn device using long-short term memory deep learning

30. Multiday cycles of heart rate are associated with seizure likelihood: An observational cohort study

31. Forecasting psychogenic non-epileptic seizure likelihood from ambulatory EEG and ECG

32. Signal quality and power spectrum analysis of remote ultra long-term subcutaneous EEG

33. Signal quality and power spectrum analysis of remote ultra long-term subcutaneous EEG

34. Non-invasive wearable seizure detection using long–short-term memory networks with transfer learning

35. Remote and Long-Term Self-Monitoring of Electroencephalographic and Noninvasive Measurable Variables at Home in Patients With Epilepsy (EEG@HOME): Protocol for an Observational Study

36. Cycles of self-reported seizure likelihood correspond to yield of diagnostic epilepsy monitoring

37. Signal quality and patient experience with wearable devices for epilepsy management

38. Machine learning and wearable devices of the future

39. Computer-assisted estimation of interictal discharge burden in idiopathic generalized epilepsy

40. A Convolutional Neural Network Model for Decoding EEG signals in a Hand-Squeeze Task1

41. Postictal suppression and seizure durations: A patient‐specific, long‐term <scp>iEEG</scp> analysis

42. Computer-assisted EEG diagnostic review for idiopathic generalized epilepsy

43. Epileptic Seizure Prediction Using Big Data and Deep Learning: Toward a Mobile System

44. Multiday Cycles of Heart Rate Modulate Seizure Likelihood at Daily, Weekly and Monthly Timescales: An Observational Cohort Study

45. Forecasting Cycles of Seizure Likelihood

46. Seizure Forecasting Using Long-Term Electroencephalography and Electrocardiogram Data

47. Bursts of seizures in long-term recordings of human focal epilepsy

48. Consistency of Long-Term Subdural Electrocorticography in Humans

49. Intracranial EEG fluctuates over months after implanting electrodes in human brain

50. TrueNorth-enabled real-time classification of EEG data for brain-computer interfacing

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