Overview
This page displays an alphabetical list of all software projects on Brain Data Science Platform. To search content on Brain Data Science Platform, visit the search page. Enter the search terms, add a filter for resource type if needed, and select how you would like the results to be ordered (for example, by relevance, by date, or by title).
All Software
- 2HELPS2B: an EEG-based risk score for seizure probability in hospitalized patients: MATLAB code and de-identified CCEMRC data behind the 2HELPS2B seizure-risk score: seizure probability by ictal-interictal-continuum EEG pattern (5,742 continuous-EEG records).
- A Primer on EEG Spectrograms: a de-identified EEG/qEEG teaching atlas: A de-identified teaching atlas of 224 labeled EEG segments, each pairing raw EEG with its qEEG spectrogram, plus MATLAB code to regenerate the paired figures. Accompanies "A Primer on EEG Spectrograms" (Ng et al., 2022).
- Automated annotation of epileptiform burden and its association with outcomes: MATLAB code and de-identified data (1,991 patients) relating automatically-quantified ictal-interictal-continuum/seizure burden on continuous EEG to discharge outcome (Zafar et al., Ann Neurol 2021).
- Continuous EEG monitoring enhances multimodal outcome prediction in hypoxic-ischemic brain injury: LASSO models predicting outcome, mortality, and disposition after cardiac arrest, showing EEG reactivity improves multimodal prognostication (373-patient cohort). MATLAB code + de-identified data.
- DDESVSFS: a screening tool for the differential diagnosis of epileptic versus functional seizures: MATLAB code and de-identified data for the DDESVSFS questionnaire-based screening tool distinguishing epileptic from functional (psychogenic) seizures (208 patients; AUC 0.93).
- EEG-based grading of immune effector cell-associated neurotoxicity syndrome: An interpretable ordinal EEG-feature score (VE-ICANS) that grades the severity of immune effector cell-associated neurotoxicity syndrome (ICANS) after CAR-T therapy. Code + de-identified data.
- Effects of epileptiform activity on discharge outcome in critically ill patients: De-identified data and a PK-PD + MALTS causal-inference pipeline reproducing the effect of untreated epileptiform-activity burden on poor discharge outcome in critically ill patients (Parikh et al., Lancet Digital Health 2023).
- Epileptiform activity and outcomes in toxic-metabolic encephalopathy: De-identified data and reproduction code for a retrospective cEEG study of ictal-interictal continuum patterns and outcomes in 121 patients with toxic-metabolic encephalopathy (MGH, 2012-2017).
- Forecasting immune effector cell-associated neurotoxicity syndrome after CAR T-cell therapy: MATLAB code and de-identified data to forecast the onset and day-by-day trajectory of ICANS after CAR T-cell therapy (combined hidden Markov model + lasso logistic regression; 199-patient cohort, leave-one-patient-out cross-validation).
- How many patients do you need? A trial-design simulation for anti-seizure treatment in acute brain injury: MATLAB/Python code and de-identified data for a simulation framework that estimates required sample sizes and effect sizes for randomized trials of anti-seizure treatment in critically ill patients (Parikh et al., Ann Clin Transl Neurol 2024).
- Interpretable quantitative criteria for evaluating interictal epileptiform discharges: MATLAB code and de-identified data for six interpretable quantitative EEG features (amplitude, duration, sharpness, slow wave, asymmetry, field) combined to classify interictal epileptiform discharges (AUC ~0.83).
- NeuroBrowser: Rapid Annotation of Interictal Epileptiform Discharges via Template Matching under Dynamic Time Warping: Ultrafast EEG template matching under Dynamic Time Warping for rapid annotation of interictal epileptiform discharges, with an open-source Python implementation and a demo dataset.
- Noise in the diagnosis of epilepsy by experts: Twenty epileptologists diagnosed 50 suspected-seizure vignettes on two occasions; a Bayesian hierarchical model decomposes diagnostic variability into signal and noise. Code + de-identified data.
- Optimal spindle detection parameters for predicting cognitive performance: De-identified sleep-spindle feature data (BDSP-linked) + cognition data + Python code to find the spindle-detection parameters that best predict cognitive performance (Adra et al., Sleep 2022).
- Philosopher's Stone: Initial version
- Prognostic significance of EEG patterns in post-cardiac arrest coma: a 1,000-patient multicenter cohort: De-identified 1,000-patient multicenter dataset (BDSP-linked) and Python code for the prognostic significance of continuous-EEG patterns after cardiac arrest, with exact Clopper-Pearson CIs and temporal-trend analysis.
- Sleep Electroencaphalography-Based Brain Age Index: Sleep EEG based brain age index is included in Luna v0.99 release.
- Time-dependent risk of seizures in critically ill patients on continuous electroencephalogram: R (mstate) and MATLAB code with de-identified data for a 3-state multistate survival model of time-dependent seizure risk on continuous EEG in critically ill patients (665 consecutive cEEGs).