datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
novae
Description
Full novae dataset, including:
All the spatial transcriptomics samples used to train Novae
Protein samples used in the article
Some Visium and Visium HD samples
Synthetic data samples
You can download this dataset from the API, see novae.load_dataset
See here the list of available models trained on this dataset.
[!NOTE]
Note that Novae was trained on the image-based spatial transcriptomics samples. This means that it was not trained on the Visium/VisiumHD samples… See the full description on the dataset page: https://huggingface.co/datasets/prism-oncology/novae.oncology-trial-strategy
Learning Clinical-Trial Strategy: Offline Policy Training for Decision Agents
Oncology trial-strategy decision episodes — the dataset for our ICML 2026 workshop paper.
Temporal dataset for offline policy training of clinical-trial-strategy decision agents, from our
ICML 2026 workshop paper, accepted at two workshops:
GenBio (Generative and Agentic AI for Biology) as "Learning Clinical-Trial Strategy: Offline
Policy Training for Decision Agents".
Offline2Online (Decision-Making… See the full description on the dataset page: https://huggingface.co/datasets/WillBolton/oncology-trial-strategy.medgemma-4b-hematologic-oncology-blind-spots
MedGemma Blind Spots: Hematologic Oncology & CAR-T Immunotherapy
A 13-probe red-team evaluation showing how Google's MedGemma-4B confidently hallucinates clinical-trial statistics, fabricates non-existent treatment regimens, and misdiagnoses lymphoma in hematologic oncology — a clinical domain absent from its documented training data.
Summary
This dataset documents failures of Google's MedGemma-4B on hematologic oncology prompts — a clinical subspecialty absent… See the full description on the dataset page: https://huggingface.co/datasets/Mateenah/medgemma-4b-hematologic-oncology-blind-spots.Medical_oncology_01
📖 Dataset Summary
This dataset contains high-fidelity, deterministic synthetic patient records for Non-Small Cell Lung Cancer (NSCLC).
Unlike traditional generative AI that "guesses" data based on existing seeds, the Anode Zero-Seed Engine generates these records from first principles using medical logic, clinical guidelines, and genomic constraints. This ensures 100% biological and clinical consistency across all longitudinal fields.
🧬 Technical Specifications &… See the full description on the dataset page: https://huggingface.co/datasets/Sampade07/Medical_oncology_01.multimodal-oncology-atlas
LH2 Data — Multimodal Oncology Dataset
A large-scale, multimodal oncology dataset built around a principle rare in the field: placing non-Caucasian patient populations at the centre, not the periphery.
Dataset Summary
The vast majority of oncology datasets used to train diagnostic, prognostic, and treatment AI models are drawn overwhelmingly from Caucasian, Western populations — a well-documented limitation that undermines model generalisability and equity in real-world… See the full description on the dataset page: https://huggingface.co/datasets/LH2-data-labs/multimodal-oncology-atlas.oncology-readability-collapse-risk-v0.3
What this dataset does
This dataset tests whether a model can detect pre-cancer instability risk from loss of signal readability rather than from stress burden alone.
The task is not cancer diagnosis.
The task is to classify whether a synthetic tissue ecology has entered readability collapse risk.
Core Stability Idea
The dataset represents a stability-transition hypothesis.
Cancer vulnerability may begin when tissue regulation loses the ability to correctly read… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/oncology-readability-collapse-risk-v0.3.africa-synth-cancer-geriatric-oncology-africa-eritrea
Geriatric Oncology Africa | Africa (Electric Sheep Africa metadata inventory)
Size category: 1K<n<10K - Formats: csv - Sector: health - Engineered by Electric Sheep Africa
TL;DR
This dataset is part of the Electric Sheep Africa catalog on Hugging Face. It is indexed for African data discovery with standardized metadata, loading guidance, provenance notes, and analyst-oriented context.
What This Dataset Covers
Health datasets help researchers… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/africa-synth-cancer-geriatric-oncology-africa-eritrea.oncology-signal-alignment-boundary-v0.4
What this dataset does
This dataset tests whether a model can detect signal-alignment failure in a synthetic tissue ecology.
The task is not cancer diagnosis.
The task is to classify whether readable biological signals can still coordinate repair.
Core Stability Idea
A tissue may still read damage, repair, immune, and metabolic signals but fail because those subsystems no longer align around coherent action.
This dataset moves beyond readability collapse.
It tests… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/oncology-signal-alignment-boundary-v0.4.oncology-missing-signal-detection-v0.6
What this dataset does
This dataset tests whether a model can detect missing-signal instability risk in a synthetic tissue ecology.
The task is not cancer diagnosis.
The task is to classify whether the observed signal set is sufficient to support stable sensing.
Core Stability Idea
A tissue may appear stable because a critical signal is absent.
Absence of signal is not the same as evidence of stability.
This dataset tests whether a model can distinguish true calm… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/oncology-missing-signal-detection-v0.6.oncology-signal-latency-boundary-v0.5
What this dataset does
This dataset tests whether a model can detect timing failure in a synthetic tissue ecology.
The task is not cancer diagnosis.
The task is to classify whether a tissue-state scenario can detect and act before the repair opportunity closes.
Core Stability Idea
A tissue may detect the correct signal, interpret it correctly, and coordinate a response, but still fail because action arrives too late.
This dataset tests the timing layer of… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/oncology-signal-latency-boundary-v0.5.oncology-precancer-constraint-geometry-v0.2
What this dataset does
This dataset tests whether a model can detect pre-cancer instability from constraint geometry rather than single-variable thresholds.
The task is not cancer diagnosis.
The task is to classify whether a synthetic tissue ecology has crossed into a persistent instability transition.
Core Stability Idea
The dataset represents a stability-transition hypothesis.
Cancer vulnerability may begin when tissue regulation loses self-correcting coherence… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/oncology-precancer-constraint-geometry-v0.2.medical-text-generation-oncology-froncology-1k
Oncology Medical Dataset — 1,000 Record Free Sample
Enterprise-grade synthetic medical data. Zero PHI. 100% HIPAA-compliant.
Quality Metrics
Metric
Score
Industry Benchmark
Trinity Consensus Score (TAS)
98.0%
85-92% typical
Inter-Annotator Agreement
0.97
0.75-0.85 typical
Macro F1
0.970.80-0.90 typical
PHI Present
None
--
Generation Method
3-LLM Trinity Ensemble
Single model typical
What's Included (Free)
1,000… See the full description on the dataset page: https://huggingface.co/datasets/WitnessDataFactory/oncology-1k.faers-oncology-drug-safety
Oncology — Drug Safety Intelligence (FAERS 2020–2025)
Version: 1.0.0 | Records: 928,991 | Source: FDA FAERS
Dataset Summary
Structured adverse event reports for oncology drugs from the FDA's FAERS
database, 2020–2025. Covers serious adverse events only (hospitalization,
life-threatening outcomes, death). Each record includes the suspect drug(s),
reported reactions (MedDRA coded), patient demographics, outcome codes,
reporter country, and seriousness flags.… See the full description on the dataset page: https://huggingface.co/datasets/RubyIntelligence/faers-oncology-drug-safety.africa-synth-cancer-pediatric-oncology-africa-all
Pediatric Oncology Africa | Africa (World Health Organization)
Size category: 1K<n<10K - Formats: csv - Sector: health - Engineered by Electric Sheep Africa
TL;DR
This dataset is part of the Electric Sheep Africa catalog on Hugging Face. It is indexed for African data discovery with standardized metadata, loading guidance, provenance notes, and analyst-oriented context.
What This Dataset Covers
Health datasets help researchers examine disease… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/africa-synth-cancer-pediatric-oncology-africa-all.Oncology_cancer_ehrprecision_oncology_synthetic_trialsprecision_oncology_genomic_variant_analysis