datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
augmented-clinical-notes
Augmented Clinical Notes
The Augmented Clinical Notes dataset is an extension of existing datasets containing 30,000 triplets from different sources:
Real clinical notes (PMC-Patients): Clinical notes correspond to patient summaries from the PMC-Patients dataset, which are extracted from PubMed Central case studies.
Synthetic dialogues (NoteChat): Synthetic patient-doctor conversations were generated from clinical notes using GPT 3.5.
Structured patient information (ours): From… See the full description on the dataset page: https://huggingface.co/datasets/AGBonnet/augmented-clinical-notes.icd10-clinical-notes
ICD-10 Multilingual Clinical Notes Dataset
A comprehensive multilingual dataset of ICD-10 diagnosis codes with clinical journal notes in 34 languages.
Author: Birger Moëll, Department of Linguistics and Philology, Uppsala University
Dataset Description
This dataset provides ICD-10 codes with:
Official diagnosis names in 34 languages (24 EU + 10 major world languages)
Sample clinical journal notes (English and Swedish)
Train/test splits for classifier training… See the full description on the dataset page: https://huggingface.co/datasets/birgermoell/icd10-clinical-notes.teacher-notes-severity
teacher-notes-severity
Synthetic dataset for training a local student-notes severity classifier (fine-tuned from Qwen/Qwen3-1.7B).
Each row is a chat-formatted prompt/completion pair: the user turn is a teacher note (single, compound,
or a cumulative running log), the assistant turn is a JSON label
{"category": "commendation|misbehavior|academic_concern", "severity": <int>, "escalate": <bool>}.
Severity scale: commendations are negative (-95..-10); routine notes 5-55; serious… See the full description on the dataset page: https://huggingface.co/datasets/jeremierostan/teacher-notes-severity.household-notes
Household and Hub reading notes
A small documentation corpus, not a benchmark.
household-note: Simplified Chinese how-tos. Each row is one failure mode (limescale vs soap scum, leftover rice, washer gasket, etc.). Diagnose first, then a short procedure, including when to stop.
hub-reading-note: English notes about using the Hugging Face Hub (model cards, safetensors, datasets, Spaces, revisions).
Use it to try load_dataset, RAG demos, or tokenizer tests. Do not treat it as… See the full description on the dataset page: https://huggingface.co/datasets/bianbian888/household-notes.mimic-iv-notesaugmented-clinical-notes
Augmented Clinical Notes
The Augmented Clinical Notes dataset is an extension of existing datasets containing 30,000 triplets from different sources:
Real clinical notes (PMC-Patients): Clinical notes correspond to patient summaries from the PMC-Patients dataset, which are extracted from PubMed Central case studies.
Synthetic dialogues (NoteChat): Synthetic patient-doctor conversations were generated from clinical notes using GPT 3.5.
Structured patient information (ours): From… See the full description on the dataset page: https://huggingface.co/datasets/johnny8808/augmented-clinical-notes.augmented-clinical-notes
Augmented Clinical Notes
The Augmented Clinical Notes dataset is an extension of existing datasets containing 30,000 triplets from different sources:
Real clinical notes (PMC-Patients): Clinical notes correspond to patient summaries from the PMC-Patients dataset, which are extracted from PubMed Central case studies.
Synthetic dialogues (NoteChat): Synthetic patient-doctor conversations were generated from clinical notes using GPT 3.5.
Structured patient information (ours): From… See the full description on the dataset page: https://huggingface.co/datasets/Vinay393/augmented-clinical-notes.teacher-notes-severity-v2
Teacher Notes Severity v2
Synthetic teacher notes labeled with category, location (in_class / outside_class), severity (-100..100, >=60 escalates) and escalate flag. 3800 train / 400 test. Generator: generate_dataset_v2.py in this repo. Continues the v1 dataset (jeremierostan/teacher-notes-severity); schema adds location.
augmented-clinical-notes
Augmented Clinical Notes
The Augmented Clinical Notes dataset is an extension of existing datasets containing 30,000 triplets from different sources:
Real clinical notes (PMC-Patients): Clinical notes correspond to patient summaries from the PMC-Patients dataset, which are extracted from PubMed Central case studies.
Synthetic dialogues (NoteChat): Synthetic patient-doctor conversations were generated from clinical notes using GPT 3.5.
Structured patient information (ours): From… See the full description on the dataset page: https://huggingface.co/datasets/Fadil369/augmented-clinical-notes.medical_notes_30k_questionsWe asked Minimax/Minimax-M3 to create 100 questions for the dataset https://huggingface.co/datasets/AGBonnet/augmented-clinical-notes.
The questions are created to cover multiple notes and trace their provenance through evidences and note IDs.
field-notes-transcription-packet
Field-notes Transcription Packet
Verified field-note transcriptions retained for the research archive.
Retained notes: 6
Featured note: NOTE-1002 — Cedar / English
Transcription window: 2023-01-18T16:20:00Z to 2023-12-15T10:00:00Z
Site counts (Cedar/Lark/Morrow/Pine): 2/2/1/1
Mean word counts (Cedar/Lark/Morrow/Pine): 422.5/362.5/360.0/480.0
augmented-clinical-notes
Augmented Clinical Notes
The Augmented Clinical Notes dataset is an extension of existing datasets containing 30,000 triplets from different sources:
Real clinical notes (PMC-Patients): Clinical notes correspond to patient summaries from the PMC-Patients dataset, which are extracted from PubMed Central case studies.
Synthetic dialogues (NoteChat): Synthetic patient-doctor conversations were generated from clinical notes using GPT 3.5.
Structured patient information (ours): From… See the full description on the dataset page: https://huggingface.co/datasets/minidiablo05/augmented-clinical-notes.icd10-clinical-notes
ICD-10 Multilingual Clinical Notes Dataset
A comprehensive multilingual dataset of ICD-10 diagnosis codes with clinical journal notes in 34 languages.
Author: Birger Moëll, Department of Linguistics and Philology, Uppsala University
Dataset Description
This dataset provides ICD-10 codes with:
Official diagnosis names in 34 languages (24 EU + 10 major world languages)
Sample clinical journal notes (English and Swedish)
Train/test splits for classifier training… See the full description on the dataset page: https://huggingface.co/datasets/Danishaqil/icd10-clinical-notes.JEP-EU-AI-Act-Mapping-Notes
JEP — EU AI Act Mapping Notes
Exploratory / non-normative / not legal advice
This dataset records limited research notes about where JEP-style signed event
structures may be relevant to documentation, traceability, or review workflows
discussed in the EU AI Act.
It does not claim that JEP provides compliance, satisfies any legal
requirement, or replaces legal, regulatory, technical, or organizational
controls.
Protocol source
JEP-Core 0.7 / draft-07:… See the full description on the dataset page: https://huggingface.co/datasets/hjs-spec/JEP-EU-AI-Act-Mapping-Notes.clinical-notes-to-fhir
SGRS-FHIR: A Preference Learning Dataset for Clinical FHIR Extraction
The first preference learning dataset for clinical FHIR extraction with structured error paths.
Key Insight
Structured extraction failures are training signal, not noise.
Unlike traditional datasets that discard generation failures, SGRS-FHIR intentionally captures both valid and invalid extractions with detailed error annotations. This enables:
Direct Preference Optimization (DPO): Train models to… See the full description on the dataset page: https://huggingface.co/datasets/ai-galileo/clinical-notes-to-fhir.synthetic-multi-med-notes-ner-v1
Multilingual Synthetic Medical Notes for NER
This dataset provides multilingual synthetic clinical notes for information extraction and NER workflows.
Dataset file
train.jsonl (JSON Lines): one example per line
Schema
Each line in train.jsonl contains:
text: synthetic medical note text
language: language of the note
entities: character-level entity annotations (text, label, start, end)
gliner_tokenized_text: tokenized note text for GLiNER-style… See the full description on the dataset page: https://huggingface.co/datasets/E3-JSI/synthetic-multi-med-notes-ner-v1.han-basic-household-help-notes-v1adaption-uganda-malaria-clinical-notes
This dataset is a remastered version of this dataset prepared using Adaption's Adaptive Data platform.
Overview
This Dataset is a clinician-informed, multilingual clinical reasoning dataset designed to support the development of adaptive AI systems for healthcare in low-resource, multilingual settings.
It captures realistic clinical workflows across Uganda, where clinician–patient interactions often occur in local languages, but clinical documentation must be in English.… See the full description on the dataset page: https://huggingface.co/datasets/Kofi24/adaption-uganda-malaria-clinical-notes.augmented-clinical-notes
Augmented Clinical Notes
The Augmented Clinical Notes dataset is an extension of existing datasets containing 30,000 triplets from different sources:
Real clinical notes (PMC-Patients): Clinical notes correspond to patient summaries from the PMC-Patients dataset, which are extracted from PubMed Central case studies.
Synthetic dialogues (NoteChat): Synthetic patient-doctor conversations were generated from clinical notes using GPT 3.5.
Structured patient information (ours): From… See the full description on the dataset page: https://huggingface.co/datasets/huzaib-khan-23/augmented-clinical-notes.medical-dialogs-notesscraped_noteshan-human-robot-interaction-notes-v1
Human–Robot Interaction Notes (Manual)
This dataset contains manually written interaction notes
describing how a humanoid agent responds to everyday human instructions.
The goal is to capture natural, imperfect, and human-like interactions
instead of idealized or synthetic commands.
Motivation
While many datasets focus on clean and optimal commands,
real-world human interaction is often ambiguous, emotional,
and context-dependent.
This dataset was created to explore how… See the full description on the dataset page: https://huggingface.co/datasets/ariefansclub/han-human-robot-interaction-notes-v1.han-robot-task-correction-notes-v1
Robot Task Correction Notes (Manual)
This dataset captures manual notes of task corrections
given by humans when a humanoid agent makes mistakes
or partially completes a task.
The focus is on realistic correction patterns
rather than perfect command execution.
Motivation
In real environments, humanoid robots rarely complete tasks perfectly
on the first attempt.
Humans naturally correct robots through short feedback,
gestures, or clarifications.
This dataset documents… See the full description on the dataset page: https://huggingface.co/datasets/ariefansclub/han-robot-task-correction-notes-v1.arcaea-num-notes
Arcaea Num Notes Dataset
wikiwikiのノート数をもとにしたデータセット。
収集コードはmain.rbを参照してください。
synthetic-clinical-notes-nl3soap_notessynthetic-clinical-notes-nl2adaption-clinical-notes-to-structured-json
This dataset is a remastered version prepared using Adaption's Adaptive Data platform.
adaption-clinical_notes_to_structured_json
This dataset contains pairs of unstructured clinical intake notes and their corresponding structured JSON representations. Each sample transforms raw patient descriptions, including demographics, symptoms, vitals, and treatments, into a standardized schema with specific fields for analysis. The content covers diverse medical scenarios ranging from minor… See the full description on the dataset page: https://huggingface.co/datasets/T3ns0rT1nk3r/adaption-clinical-notes-to-structured-json.endocrinology_transcription_and_notesaugmented-clinical-notes
Augmented Clinical Notes
The Augmented Clinical Notes dataset is an extension of existing datasets containing 30,000 triplets from different sources:
Real clinical notes (PMC-Patients): Clinical notes correspond to patient summaries from the PMC-Patients dataset, which are extracted from PubMed Central case studies.
Synthetic dialogues (NoteChat): Synthetic patient-doctor conversations were generated from clinical notes using GPT 3.5.
Structured patient information (ours):… See the full description on the dataset page: https://huggingface.co/datasets/Afrinzaman98/augmented-clinical-notes.