pat2vec.pat2vec_get_methods.get_method_core02

Functions

calculate_core_o2_features(features_data[, ...])

Calculates O2 saturation features from CORE_SpO2 observations.

clean_observation_value(value)

Cleans an observation value to be used as a feature name.

get_core_02(current_pat_client_id_code, ...)

Retrieves CORE_SpO2 features for a patient within a date range.

search_core_o2_observations([...])

Searches for CORE_SpO2 observation data within a date range.
pat2vec.pat2vec_get_methods.get_method_core02.search_core_o2_observations(cohort_searcher_with_terms_and_search=None, client_id_codes=None, observations_time_field='observationdocument_recordeddtm', start_year='1995', start_month='01', start_day='01', end_year='2025', end_month='12', end_day='12', search_term='CORE_SpO2', additional_custom_search_string=None)[source]

Searches for CORE_SpO2 observation data within a date range.

Uses a cohort searcher to find CORE_SpO2 observation data for specified patients within a given date range.

Parameters:

  • cohort_searcher_with_terms_and_search (Optional[Callable]) – The function for cohort searching. Defaults to None.

  • client_id_codes (Optional[Union[str, List[str]]]) – The client ID code(s) of the patient(s). Defaults to None.

  • observations_time_field (str) – The timestamp field for filtering observations. Defaults to ‘observationdocument_recordeddtm’.

  • start_year (str) – Start year for the search. Defaults to ‘1995’.

  • start_month (str) – Start month for the search. Defaults to ‘01’.

  • start_day (str) – Start day for the search. Defaults to ‘01’.

  • end_year (str) – End year for the search. Defaults to ‘2025’.

  • end_month (str) – End month for the search. Defaults to ‘12’.

  • end_day (str) – End day for the search. Defaults to ‘12’.

  • search_term (str) – The observation type to search for. Defaults to “CORE_SpO2”.

  • additional_custom_search_string (Optional[str]) – An additional string to append to the search query. Defaults to None.

Returns:

A DataFrame containing the raw CORE_SpO2 observation data.

Return type:

pd.DataFrame

Raises:

ValueError – If essential arguments are None.

pat2vec.pat2vec_get_methods.get_method_core02.clean_observation_value(value)[source]

Cleans an observation value to be used as a feature name.

Replaces characters that are invalid in column names.

Parameters:

value (str) – The original observation value.

Returns:

The cleaned value suitable for use as a column name,

or None if the input is NaN.

Return type:

Optional[str]

pat2vec.pat2vec_get_methods.get_method_core02.calculate_core_o2_features(features_data, search_term='CORE_SpO2')[source]

Calculates O2 saturation features from CORE_SpO2 observations.

Creates binary features for each unique observation value found in the data.

Parameters:

  • features_data (pd.DataFrame) – DataFrame containing CORE_SpO2 observations.

  • search_term (str) – The observation type being processed. Defaults to “CORE_SpO2”.

Returns:

A dictionary of calculated binary features.

Return type:

Dict[str, int]

pat2vec.pat2vec_get_methods.get_method_core02.get_core_02(current_pat_client_id_code, target_date_range, pat_batch, config_obj=None, cohort_searcher_with_terms_and_search=None)[source]

Retrieves CORE_SpO2 features for a patient within a date range.

This function fetches CORE_SpO2 (oxygen saturation) data, either from a pre-loaded batch or by searching, and then creates binary features for each unique observation value.

Parameters:

  • current_pat_client_id_code (str) – The client ID code of the patient.

  • target_date_range (Tuple) – A tuple representing the target date range.

  • pat_batch (pd.DataFrame) – The DataFrame containing patient data for batch mode.

  • config_obj (Optional[object]) – Configuration object containing batch_mode and other settings. Defaults to None.

  • cohort_searcher_with_terms_and_search (Optional[Callable]) – The function for cohort searching. Defaults to None.

Returns:

A DataFrame containing CORE_SpO2 features for the

specified patient. If no data is found, a DataFrame with only the ‘client_idcode’ is returned.

Return type:

pd.DataFrame

Raises:

ValueError – If config_obj is None, or if cohort_searcher_with_terms_and_search is None when not in batch mode.