Datasetpublic

AmareshHebbar/symptom-diagnoser-sft

Symptom to Diagnosis (ChatDoctor-200k) Part of the AxisMapper Medical AI Suite — 16 domain-specific SFT datasets for fine-tuning medical LLMs. Built by AmareshHebbar | Studio Ilios / Humanova Minds What this dataset does Patient symptom descriptions → differential diagnosis with ICD-10 codes Why download this Build clinical decision support chatbots, symptom checkers, or medical question-answering systems. Largest dataset in the AxisMapper suite.… See the full description on the dataset page: https://huggingface.co/datasets/AmareshHebbar/symptom-diagnoser-sft.

sourceHugging Faceapache-2.0updated 3mo agoView on Hugging Face

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Dataset Card

Symptom to Diagnosis (ChatDoctor-200k)

Part of the [AxisMapper Medical AI Suite](https://huggingface.co/collections/AmareshHebbar/axiomapper-medical-ai-suite) — 16 domain-specific SFT datasets for fine-tuning medical LLMs.

Built by [AmareshHebbar](https://huggingface.co/AmareshHebbar) | Studio Ilios / Humanova Minds

What this dataset does

Patient symptom descriptions → differential diagnosis with ICD-10 codes

Why download this

Build clinical decision support chatbots, symptom checkers, or medical question-answering systems. Largest dataset in the AxisMapper suite.

Dataset stats

Split	Rows
Train	95,573
Validation	11,947
Test	11,947
Total	119,467

Data format

Every row is a messages list in chat format — compatible with Unsloth, TRL SFTTrainer, LLaMA-Factory, and any OpenAI-style fine-tuning pipeline:

json

{
  "messages": [
    {"role": "system",    "content": "You are a ..."},
    {"role": "user",      "content": "I have had severe chest pain radiating to my left arm for the past 30 minutes, along with sweating and nausea."},
    {"role": "assistant", "content": "This presentation is highly concerning for Acute Myocardial Infarction (I21.9). Call emergency services immediately. Differential includes unstable angina (I20.0) and aortic dissection (I71.0)."}
  ]
}

Data source

avaliev/chat_doctor — 200k real patient-doctor Q&A conversations → https://huggingface.co/datasets/avaliev/chat_doctor

All data is extracted from authoritative public sources. No LLM-generated or synthetic content.

Who should use this

AI health app developers, clinical NLP researchers, medical chatbot builders.

Quick start

python

from datasets import load_dataset

ds = load_dataset("AmareshHebbar/symptom-diagnoser-sft")
print(ds["train"][0])

Fine-tuning example (Unsloth)

python

from unsloth import FastLanguageModel
from trl import SFTTrainer
from datasets import load_dataset

model, tokenizer = FastLanguageModel.from_pretrained(
    model_name="unsloth/Qwen2.5-3B-Instruct",
    max_seq_length=2048,
    load_in_4bit=True,
)

dataset = load_dataset("AmareshHebbar/symptom-diagnoser-sft", split="train")

trainer = SFTTrainer(
    model=model,
    tokenizer=tokenizer,
    train_dataset=dataset,
    dataset_text_field="messages",
    max_seq_length=2048,
)
trainer.train()

Related datasets in this collection

Dataset	Task	Rows
icd10-coder-sft	ICD-10-CM coding	74.7k
symptom-diagnoser-sft	Symptom → diagnosis	119k
clinical-summarizer-sft	SOAP summarization	30k
discharge-qa-sft	Discharge summary QA	30k
pmjay-classifier-sft	PM-JAY packages	11.1k
radiology-coder-sft	Radiology coding	25k
medical-ner-sft	Clinical NER	16.7k
hindi-medical-sft	Hindi medical QA	19.7k

Citation

bibtex

@misc{axiomapper2026,
  author    = {Hebbar, Amaresh},
  title     = {AxisMapper: Medical AI Fine-tuning Dataset Suite},
  year      = {2026},
  publisher = {HuggingFace},
  url       = {https://huggingface.co/collections/AmareshHebbar/axiomapper-medical-ai-suite}
}

AxisMapper is an open-source project. Star the repo, open issues, and contribute at [GitHub](https://github.com/amareshhebbar/AxisMapper).