pyhealth.tasks.drug_recommendation

pyhealth.tasks.drug_recommendation.drug_recommendation_mimic3_fn(patient)

Processes a single patient for the drug recommendation task.

Drug recommendation aims at recommending a set of drugs given the patient health history (e.g., conditions and procedures).

Parameters:

patient (Patient) – a Patient object

Returns:

a list of samples, each sample is a dict with patient_id, visit_id,

and other task-specific attributes as key, like this {

”patient_id”: xxx, “visit_id”: xxx, “conditions”: [list of diag in visit 1, list of diag in visit 2, …, list of diag in visit N], “procedures”: [list of prod in visit 1, list of prod in visit 2, …, list of prod in visit N], “drugs_hist”: [list of drug in visit 1, list of drug in visit 2, …, list of drug in visit (N-1)], “drugs”: list of drug in visit N, # this is the predicted target

}

Return type:

samples

Examples

>>> from pyhealth.datasets import MIMIC3Dataset
>>> mimic3_base = MIMIC3Dataset(
...    root="/srv/local/data/physionet.org/files/mimiciii/1.4",
...    tables=["DIAGNOSES_ICD", "PROCEDURES_ICD", "PRESCRIPTIONS"],
...    code_mapping={"ICD9CM": "CCSCM"},
... )
>>> from pyhealth.tasks import drug_recommendation_mimic3_fn
>>> mimic3_sample = mimic3_base.set_task(drug_recommendation_mimic3_fn)
>>> mimic3_sample.samples[0]
{
    'visit_id': '174162',
    'patient_id': '107',
    'conditions': [['139', '158', '237', '99', '60', '101', '51', '54', '53', '133', '143', '140', '117', '138', '55']],
    'procedures': [['4443', '4513', '3995']],
    'drugs_hist': [[]],
    'drugs': ['0000', '0033', '5817', '0057', '0090', '0053', '0', '0012', '6332', '1001', '6155', '1001', '6332', '0033', '5539', '6332', '5967', '0033', '0040', '5967', '5846', '0016', '5846', '5107', '5551', '6808', '5107', '0090', '5107', '5416', '0033', '1150', '0005', '6365', '0090', '6155', '0005', '0090', '0000', '6373'],
}

pyhealth.tasks.drug_recommendation.drug_recommendation_mimic4_fn(patient)

Processes a single patient for the drug recommendation task.

Drug recommendation aims at recommending a set of drugs given the patient health history (e.g., conditions and procedures).

Parameters:

patient (Patient) – a Patient object

Returns:

a list of samples, each sample is a dict with patient_id, visit_id,

and other task-specific attributes as key {

”patient_id”: xxx, “visit_id”: xxx, “conditions”: [list of diag in visit 1, list of diag in visit 2, …, list of diag in visit N], “procedures”: [list of prod in visit 1, list of prod in visit 2, …, list of prod in visit N], “drugs_hist”: [list of drug in visit 1, list of drug in visit 2, …, list of drug in visit (N-1)], “drugs”: list of drug in visit N, # this is the predicted target

}

Return type:

samples

Examples

>>> from pyhealth.datasets import MIMIC4Dataset
>>> mimic4_base = MIMIC4Dataset(
...     root="/srv/local/data/physionet.org/files/mimiciv/2.0/hosp",
...     tables=["diagnoses_icd", "procedures_icd"],
...     code_mapping={"ICD10PROC": "CCSPROC"},
... )
>>> from pyhealth.tasks import drug_recommendation_mimic4_fn
>>> mimic4_sample = mimic4_base.set_task(drug_recommendation_mimic4_fn)
>>> mimic4_sample.samples[0]
[{'visit_id': '130744', 'patient_id': '103', 'conditions': [['42', '109', '19', '122', '98', '663', '58', '51']], 'procedures': [['1']], 'label': [['2', '3', '4']]}]

pyhealth.tasks.drug_recommendation.drug_recommendation_eicu_fn(patient)

Processes a single patient for the drug recommendation task.

Drug recommendation aims at recommending a set of drugs given the patient health history (e.g., conditions and procedures).

Parameters:

patient (Patient) – a Patient object

Returns:

a list of samples, each sample is a dict with patient_id, visit_id,

and other task-specific attributes as key

Return type:

samples

Examples

>>> from pyhealth.datasets import eICUDataset
>>> eicu_base = eICUDataset(
...     root="/srv/local/data/physionet.org/files/eicu-crd/2.0",
...     tables=["diagnosis", "medication"],
...     code_mapping={},
...     dev=True
... )
>>> from pyhealth.tasks import drug_recommendation_eicu_fn
>>> eicu_sample = eicu_base.set_task(drug_recommendation_eicu_fn)
>>> eicu_sample.samples[0]
[{'visit_id': '130744', 'patient_id': '103', 'conditions': [['42', '109', '98', '663', '58', '51']], 'procedures': [['1']], 'label': [['2', '3', '4']]}]

pyhealth.tasks.drug_recommendation.drug_recommendation_omop_fn(patient)

Processes a single patient for the drug recommendation task.

Drug recommendation aims at recommending a set of drugs given the patient health history (e.g., conditions and procedures).

Parameters:

patient (Patient) – a Patient object

Returns:

a list of samples, each sample is a dict with patient_id, visit_id,

and other task-specific attributes as key

Return type:

samples

Examples

>>> from pyhealth.datasets import OMOPDataset
>>> omop_base = OMOPDataset(
...     root="https://storage.googleapis.com/pyhealth/synpuf1k_omop_cdm_5.2.2",
...     tables=["condition_occurrence", "procedure_occurrence"],
...     code_mapping={},
... )
>>> from pyhealth.tasks import drug_recommendation_omop_fn
>>> omop_sample = omop_base.set_task(drug_recommendation_eicu_fn)
>>> omop_sample.samples[0]
[{'visit_id': '130744', 'patient_id': '103', 'conditions': [['42', '109', '98', '663', '58', '51'], ['98', '663', '58', '51']], 'procedures': [['1'], ['2', '3']], 'label': [['2', '3', '4'], ['0', '1', '4', '5']]}]