ai_cdss.DataLoader#
- class ai_cdss.DataLoader(rgs_mode='plus')[source]#
Loads data from database and CSV files for the Clinical Decision Support System.
- Args:
rgs_mode (str, optional): Mode for fetching RGS data. Default is “plus”.
Methods
fetch_and_validate_patients(study_ids)Fetch patient data for the given study IDs and validate that patients exist.
load_patient_data(patient_list)Load all data specific to a patient clinical trial.
load_patient_subscales(patient_list)Load and decode patient clinical scale data for the given patient list.
load_ppf_data(patient_list)Load PPF (precomputed patient-protocol fit) data from internal storage.
load_protocol_attributes([file_path])Load protocol attributes from internal storage or a specified file path.
Load protocol similarity data from internal storage.
load_session_data(patient_list)Load session data from the RGS interface.
load_timeseries_data(patient_list)Load timeseries data for the given patient list.
- load_patient_data(patient_list)[source]#
Load all data specific to a patient clinical trial.
- Return type:
Union[DataFrame,DataUnit]
- Args:
patient_list (List[int]): List of patient IDs.
- Returns:
Union[pd.DataFrame, DataUnit]: Patient data as a DataFrame or DataUnit.
- load_session_data(patient_list)[source]#
Load session data from the RGS interface.
- Return type:
Union[DataFrame,DataUnit]
- Args:
patient_list (List[int]): List of patient IDs.
- Returns:
Union[pd.DataFrame, DataUnit]: Session data as a DataFrame or DataUnit.
- load_timeseries_data(patient_list)[source]#
Load timeseries data for the given patient list.
- Return type:
Union[DataFrame,DataUnit]
- Args:
patient_list (List[int]): List of patient IDs.
- Returns:
Union[pd.DataFrame, DataUnit]: Timeseries data as a DataFrame or DataUnit.
- load_ppf_data(patient_list)[source]#
Load PPF (precomputed patient-protocol fit) data from internal storage.
- Return type:
Union[DataFrame,DataUnit]
- Args:
patient_list (List[int]): List of patient IDs.
- Returns:
Union[pd.DataFrame, DataUnit]: PPF data as a DataFrame or DataUnit.
- load_patient_subscales(patient_list)[source]#
Load and decode patient clinical scale data for the given patient list.
- Return type:
Union[DataFrame,DataUnit]
- Args:
patient_list (List[int]): List of patient IDs.
- Returns:
Union[pd.DataFrame, DataUnit]: Decoded patient scale data indexed by PATIENT_ID.
- load_protocol_attributes(file_path=None)[source]#
Load protocol attributes from internal storage or a specified file path.
- Args:
file_path (str, optional): Path to the protocol attributes file.
- Returns:
pd.DataFrame: Protocol attributes data.
- load_protocol_similarity()[source]#
Load protocol similarity data from internal storage.
- Returns:
pd.DataFrame: Protocol similarity data with columns: PROTOCOL_ID_1, PROTOCOL_ID_2, SIMILARITY_SCORE.
- fetch_and_validate_patients(study_ids)[source]#
Fetch patient data for the given study IDs and validate that patients exist.
- Return type:
List[int]
- Args:
study_ids (List[int]): List of study cohort identifiers to fetch patients for.
- Returns:
List[int]: List of patient IDs associated with the provided study IDs.
- Raises:
ValueError: If no patients are found for the given study IDs.