Omkar2118/datasets huggingface dataset:
SciTail

The **SciTail** dataset is an entailment dataset created from multiple-choice science exams and web sentences. Each question and the correct answer choice are converted into an assertive statement to form the hypothesis. We use information retrieval to obtain relevant text from a large text corpus of web sentences, and use these sentences as a premise P. We crowdsource the annotation of such premise-hypothesis pair as supports (entails) or not (neutral), in order to create the SciTail dataset. The dataset contains 27,026 examples with 10,101 examples with entails label and 16,925 examples with neutral label.

Source: [Allen Institute for AI](https://allenai.org/data/scitail)
Image source: [Allen Institute for AI](https://allenai.org/data/scitail)
CHB-MIT
Full name: CHB-MIT Scalp EEG

The **CHB-MIT** dataset is a dataset of EEG recordings from pediatric subjects with intractable seizures. Subjects were monitored for up to several days following withdrawal of anti-seizure mediation in order to characterize their seizures and assess their candidacy for surgical intervention. The dataset contains 23 patients divided among 24 cases (a patient has 2 recordings, 1.5 years apart). The dataset consists of 969 Hours of scalp EEG recordings with 173 seizures. There exist various types of seizures in the dataset (clonic, atonic, tonic). The diversity of patients (Male, Female, 10-22 years old) and different types of seizures contained in the datasets are ideal for assessing the performance of automatic seizure detection methods in realistic settings.

Source: [Learning Robust Features using Deep Learning for Automatic Seizure Detection](https://arxiv.org/abs/1608.00220)
Image Source: [https://archive.physionet.org/pn6/chbmit/](https://archive.physionet.org/pn6/chbmit/)
2010 i2b2/VA
Full name: 2010 i2b2/VA

**2010 i2b2/VA** is a biomedical dataset for relation classification and entity typing.