Datasetpublic

aryang2005/symptom_to_diagnosis

Dataset Summary This dataset contains natural language descriptions of symptoms labeled with 22 corresponding diagnoses. Gretel/symptom_to_diagnosis provides 1065 symptom descriptions in the English language labeled with 22 diagnoses, focusing on fine-grained single-domain diagnosis. Data Fields Each row contains the following fields: input_text : A string field containing symptoms output_text : A string field containing a diagnosis Example: { "output_text":… See the full description on the dataset page: https://huggingface.co/datasets/aryang2005/symptom_to_diagnosis.

sourceHugging Faceapache-2.0updated 7mo agoView on Hugging Face

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Dataset Card

Dataset Summary

This dataset contains natural language descriptions of symptoms labeled with 22 corresponding diagnoses. Gretel/symptom_to_diagnosis provides 1065 symptom descriptions in the English language labeled with 22 diagnoses, focusing on fine-grained single-domain diagnosis.

Data Fields

Each row contains the following fields:

—input_text : A string field containing symptoms
—output_text : A string field containing a diagnosis

Example:

{
"output_text": "drug reaction",
"input_text": "I've been having headaches and migraines, and I can't sleep. My whole body shakes and twitches. Sometimes I feel lightheaded."
}

Diagnoses

This table contains the count of each diagnosis in the train and test splits.

	Diagnosis	train.jsonl	test.jsonl
0	drug reaction	40	8
1	allergy	40	10
2	chicken pox	40	10
3	diabetes	40	10
4	psoriasis	40	10
5	hypertension	40	10
6	cervical spondylosis	40	10
7	bronchial asthma	40	10
8	varicose veins	40	10
9	malaria	40	10
10	dengue	40	10
11	arthritis	40	10
12	impetigo	40	10
13	fungal infection	39	9
14	common cold	39	10
15	gastroesophageal reflux disease	39	10
16	urinary tract infection	39	9
17	typhoid	38	9
18	pneumonia	37	10
19	peptic ulcer disease	37	10
20	jaundice	33	7
21	migraine	32	10

Data Splits

The data is split to 80% train (853 examples, 167kb) and 20% test (212 examples, 42kb).

Dataset Creation

Data was filtered to remove unwanted categories and updated using an LLM to create language more consistent with how a patient would describe symptoms in natural language to a doctor.

Source Data

This dataset was adapted based on the Symptom2Disease dataset from Kaggle.

Personal and Sensitive Information

The symptoms in this dataset were modified from their original format using an LLM and do not contain personal data.

Limitations

This dataset is licensed Apache 2.0 and free for use.