Datasets:
The dataset viewer is not available for this split.
Error code: FeaturesError
Exception: ValueError
Message: Failed to convert pandas DataFrame to Arrow Table from file hf://datasets/ivanpodd/S-OH@5ab8f51576bdcb51d1093070427971b66dd339e1/S-OH_data_dict.json.
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 247, in compute_first_rows_from_streaming_response
iterable_dataset = iterable_dataset._resolve_features()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 4376, in _resolve_features
features = _infer_features_from_batch(self.with_format(None)._head())
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2658, in _head
return next(iter(self.iter(batch_size=n)))
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2836, in iter
for key, pa_table in ex_iterable.iter_arrow():
^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2374, in _iter_arrow
yield from self.ex_iterable._iter_arrow()
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 536, in _iter_arrow
for key, pa_table in iterator:
^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 419, in _iter_arrow
for key, pa_table in self.generate_tables_fn(**gen_kwags):
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 303, in _generate_tables
raise ValueError(
ValueError: Failed to convert pandas DataFrame to Arrow Table from file hf://datasets/ivanpodd/S-OH@5ab8f51576bdcb51d1093070427971b66dd339e1/S-OH_data_dict.json.Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
Scent of Health (S-OH) Dataset
The Scent of Health (S-OH) dataset is the largest public clinical electronic nose (eNose) collection for non-invasive disease screening via exhaled breath analysis. It comprises 1,234 patients across nine diagnostic groups (healthy controls and eight diseases), each providing a 17-channel multivariate time series of breath measurements.
| Property | Value |
|---|---|
| Patients | 1,234 |
| Diagnostic groups | 9 (healthy + 8 diseases) |
| Time series channels | 17 (eNose sensors) + auxiliary sensors |
| Sampling rate | 0.4 Hz |
| Duration per sample | 895 seconds (~15 minutes) |
| Collection period | 13 consecutive weeks |
| Clinical sites | 2 |
Diagnostic Groups
| ICD-10 Code | Diagnosis | Count |
|---|---|---|
| Z00 | Healthy controls | 256 |
| E11 | Diabetes mellitus type II | 128 |
| K29 | Gastritis and duodenitis | 138 |
| K76 | Non-alcoholic fatty liver disease | 128 |
| B18 | Hepatitis B/C | 138 |
| C34 | Lung cancer | 100 |
| N18 | Chronic renal failure | 128 |
| J44 | COPD | 100 |
| A15 | Respiratory tuberculosis | 118 |
| Total | 1,234 |
Demographics:
- Age range: 18–89 years (mean 53.9, std 13.4)
- Gender: 690 female (55.9%), 544 male (44.1%)
Dataset Structure
File 1: S-OH_metadata.csv
CSV file containing patient metadata with the following columns:
| Column | Description |
|---|---|
Patient_id |
Unique patient identifier |
Patient_age |
Age in years |
Patient_gender |
Gender (male or female) |
Diagnosis |
ICD-10 diagnosis code |
D_class |
Disease class (0–8) |
D_bin_class |
Binary class for one-vs-rest classification |
Datetime |
Collection timestamp |
Week |
Collection week (1–13) |
Site |
Clinical site (MONIKI or CRIT) |
File 2: S-OH_data_dict.json
JSON dictionary where each key is a patient ID (as string) with the following structure:
{
"patient_id": int,
"patient_diag_class": int,
"startDateTime": "ISO timestamp",
"startTimeGases": int,
"endTimeGases": int,
"durationSec": int,
"sensors": [
{
"id": "enose",
"sampleRate": 0.4,
"channels": [
{"id": "R1", "samples": [float, ...]},
{"id": "R2", "samples": [float, ...]},
...
{"id": "R17", "samples": [float, ...]},
{"id": "humidity", "samples": [float, ...]},
{"id": "temperature", "samples": [float, ...]}
]
},
{
"id": "ze03",
"sampleRate": 0.4,
"channels": [{"id": "0", "samples": [float, ...]}]
},
{
"id": "mhz14",
"sampleRate": 0.4,
"channels": [{"id": "0", "samples": [float, ...]}]
},
{
"id": "ze08",
"sampleRate": 0.4,
"channels": [{"id": "0", "samples": [float, ...]}]
},
{
"id": "bme280",
"sampleRate": 0.4,
"channels": [
{"id": "pressure", "samples": [float, ...]},
{"id": "temperature", "samples": [float, ...]},
{"id": "humidity", "samples": [float, ...]}
]
}
]
}
eNose Channels (17 channels)
The eNose sensor array consists of 17 channels printed on a single chip:
| Channel ID | Material |
|---|---|
| R1–R17 | ZnO and metal-doped ZnO (In-ZnO, Ag-ZnO, Ce-ZnO, Ni-ZnO) |
Auxiliary Sensors
| Sensor ID | Measurements |
|---|---|
| ze03 | Ozone (O₃) |
| mhz14 | Carbon dioxide (CO₂) |
| ze08 | Carbon monoxide (CO) |
| bme280 | Pressure, temperature, humidity |
Temporal Train/Test Splits
The dataset includes explicit temporal splits to enable drift-aware evaluation. For each disease, test weeks were selected to be temporally separated from training weeks, simulating real-world deployment conditions.
Ethics
The study protocol was approved by the Local Ethics Committee at Moscow Regional Research and Clinical Institute (MONIKI) and Central Research Institute of Tuberculosis (CRIT).
All participants provided written informed consent.
Citation
If you use this dataset in your research, please cite:
License
This dataset is released under the MIT License. You are free to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the dataset, subject to the following conditions:
Permission is hereby granted, free of charge, to any person obtaining a copy of this dataset and associated documentation files (the "Dataset"), to deal in the Dataset without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Dataset, and to permit persons to whom the Dataset is furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Dataset.
THE DATASET IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE DATASET OR THE USE OR OTHER DEALINGS IN THE DATASET.
Contact
For questions or issues, please open an issue on this repository or contact the authors (see paper for details).
- Downloads last month
- 80