Datasets:
Dataset Viewer
The dataset viewer is not available for this subset.
Cannot get the split names for the config 'default' of the dataset.
Exception: SplitsNotFoundError
Message: The split names could not be parsed from the dataset config.
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 286, in get_dataset_config_info
for split_generator in builder._split_generators(
~~~~~~~~~~~~~~~~~~~~~~~~~^
StreamingDownloadManager(base_path=builder.base_path, download_config=download_config)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
)
^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/tsfile/tsfile.py", line 271, in _split_generators
scan = self._scan_metadata(all_files)
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/tsfile/tsfile.py", line 318, in _scan_metadata
with self._open_reader(file) as reader:
~~~~~~~~~~~~~~~~~^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/tsfile/tsfile.py", line 742, in _open_reader
return TsFileReader(file)
File "tsfile/tsfile_reader.pyx", line 364, in tsfile.tsfile_reader.TsFileReaderPy.__init__
File "tsfile/tsfile_reader.pyx", line 367, in tsfile.tsfile_reader.TsFileReaderPy.init_reader
File "tsfile/tsfile_py_cpp.pyx", line 789, in tsfile.tsfile_py_cpp.tsfile_reader_new_c
File "tsfile/tsfile_py_cpp.pyx", line 55, in tsfile.tsfile_py_cpp.check_error
tsfile.exceptions.FileOpenError: 28: Failed to open file
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/config/split_names.py", line 68, in compute_split_names_from_streaming_response
for split in get_dataset_split_names(
~~~~~~~~~~~~~~~~~~~~~~~^
path=dataset,
^^^^^^^^^^^^^
config_name=config,
^^^^^^^^^^^^^^^^^^^
token=hf_token,
^^^^^^^^^^^^^^^
)
^
File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 340, in get_dataset_split_names
info = get_dataset_config_info(
path,
...<6 lines>...
**config_kwargs,
)
File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 291, in get_dataset_config_info
raise SplitsNotFoundError("The split names could not be parsed from the dataset config.") from err
datasets.inspect.SplitsNotFoundError: The split names could not be parsed from the dataset config.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.
HLT-009 Synthetic Continuous Vital Sign Monitoring Dataset (Sample Preview) (TsFile)
Apache TsFile version of xpertsystems/hlt009-sample.
Overview
A fully synthetic ICU continuous vital sign monitoring dataset combining 12-stream time-series vitals (HR/SpO2/RR/NBP/IBP/Temp/EtCO2/CVP/CO), alarm event logs with true/false labels, intervention logs (medication boluses, ventilator adjustments, code events), and 53-column episode-level summary data — calibrated to MIMIC-IV / eICU-CRD benchmarks with APACHE-II, SOFA, NEWS2, qSOFA, and CCI severity scoring.
- Tables: 4 TsFile table(s), 26,888 rows in total.
alarm_events: 166 rows, 2022-03-19 15:20:00 → 2023-09-19 22:15:00 (UTC)episode_summary: 25 rows, 1970-01-01 00:00:00 → 1970-01-01 00:00:00.024000 (UTC)interventions: 20 rows, 1970-01-01 00:00:00 → 2023-09-19 14:23:03.165000 (UTC)vitals_timeseries: 26,677 rows, 2022-03-15 00:00:00 → 2023-12-07 06:30:00 (UTC)
Schema (TsFile structure)
alarm_events.tsfile
- Time (INT64, milliseconds) — the source
alarm_onset_tscolumn. - TAG: none — the table is stored as a single device.
- FIELD (14):
alarm_id(string),episode_id(string),alarm_type(string),alarm_priority(string),alarm_duration_sec(int64),true_alarm_flag(int64),false_alarm_subtype(string),response_time_min(double),intervention_triggered(int64),override_flag(int64),limit_at_alarm_low(double),limit_at_alarm_high(double),alarm_cascade_id(int64),shift(string)
episode_summary.tsfile
- Time (INT64, milliseconds) — synthetic row index over the stable source order; this table has no clock column.
- TAG: none — the table is stored as a single device.
- FIELD (54):
episode_id(string),monitoring_setting(string),icu_unit_type(string),admit_dt(string),discharge_dt(string),episode_duration_days(double),bed_id(string),age(int64),sex(string),apache2_score(int64),sofa_score(int64),sofa_at_discharge(int64),primary_dx_group(string),cci_score(int64),ventilation_status(int64),vasopressor_flag(int64),rrt_flag(int64),has_arterial_line(int64),has_central_line(int64),has_pa_catheter(int64),trajectory(string),monitor_manufacturer(string),rpm_device_type(double),lead_configuration(string),device_uptime_pct(double),connectivity_drops(int64),true_alarm_rate(double),total_alarms(int64),alarms_per_patient_day(double),actionable_alarm_rate(double),alarm_override_rate(double),median_response_time_min(double),alarm_limit_modification_count(int64),alarm_cascade_count(int64),fatigue_index_score(double),news2_max(double),news2_mean(double),qsofa_max(int64),deterioration_6h_label(int64),in_hospital_mortality(int64),readmission_30d(int64),rapid_response_event(int64),sqi_hr_bpm(double),sqi_spo2_pct(double),sqi_rr_bpm(double),sqi_nbp_sys_mmhg(double),sqi_nbp_dia_mmhg(double),sqi_nbp_map_mmhg(double),sqi_ibp_sys_mmhg(double),sqi_ibp_dia_mmhg(double),sqi_temp_c(double),sqi_etco2_mmhg(double),sqi_cvp_mmhg(double),sqi_cardiac_output_lpm(double)
interventions.tsfile
- Time (INT64, milliseconds) — the source
intervention_tscolumn. - TAG: none — the table is stored as a single device.
- FIELD (10):
intervention_id(string),episode_id(string),intervention_type(string),alarm_trigger_id(string),latency_min(double),drug_class(string),dose_delta(double),vent_param_changed(string),rosc_flag(double),rapid_response_team_id(double)
vitals_timeseries.tsfile
- Time (INT64, milliseconds) — the source
timestampcolumn. - TAG: none — the table is stored as a single device.
- FIELD (18):
episode_id(string),hr_bpm(double),spo2_pct(double),rr_bpm(double),nbp_sys_mmhg(double),nbp_dia_mmhg(double),nbp_map_mmhg(double),ibp_sys_mmhg(double),ibp_dia_mmhg(double),temp_c(double),etco2_mmhg(double),cvp_mmhg(double),cardiac_output_lpm(double),artifact_flag(int64),news2_score(double),qsofa_score(double),news2_roll_max_4h(double),news2_rate_of_rise(double)
Conversion notes
- One TsFile per source CSV (4 tables). Every table is stored as a single device, so all source columns (episode/acility ids, alarm ids, device vendors) are FIELDs.
- Time = the source timestamp column parsed as INT64 milliseconds:
timestamp(5-minute vitals grid),alarm_onset_ts,intervention_ts.episode_summaryis an episode-level table with no per-row clock, so its Time is a synthetic row index (0..N-1). - No column is dropped.
Usage
Install the Apache TsFile Python SDK (pip install tsfile) and read a converted file:
from pathlib import Path
from tsfile import TsFileReader
path = Path("alarm_events.tsfile")
with TsFileReader(str(path)) as reader:
schemas = reader.get_all_table_schemas()
print("tables:", list(schemas))
table_name = next(iter(schemas))
table = schemas[table_name]
columns = [column.get_column_name() for column in table.get_columns()]
print("columns:", columns)
field_names = [
column.get_column_name()
for column in table.get_columns()
if column.get_column_name() not in {"Time", "time"}
]
if field_names:
with reader.query_table(table_name, field_names[:3], batch_size=1024) as result:
batch = result.read_arrow_batch()
if batch is not None:
print(batch.to_pandas().head())
Source & license
- Original dataset:
xpertsystems/hlt009-sample - Source card title / publisher: HLT-009 Synthetic Continuous Vital Sign Monitoring Dataset (Sample Preview)
- License: cc-by-nc-4.0 (as declared by the original dataset).
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