clean up tasks;

need to further explain usage

pyhealth/tasks/drug_recommendation.py

@@ -1,31 +1,20 @@
-import sys
-
 from pyhealth.data import Patient, Visit
 
-# TODO: remove this hack later
-sys.path.append("/home/chaoqiy2/github/PyHealth-OMOP")
-
 
 def drug_recommendation_mimic3_fn(patient: 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).
 
- Process a single patient for the drug recommendation task.
-
  Args:
  patient: a Patient object
 
  Returns:
  samples: a list of samples, each sample is a dict with patient_id, visit_id,
  and other task-specific attributes as key
 
- Note that a patient may be converted to multiple samples, e.g., a patient with
- three visits may be converted to three samples ([visit 1], [visit 1, visit 2],
- [visit 1, visit 2, visit 3]). Patients can also be excluded from the task
- dataset by returning an empty list.
- 
- **Example:**
+ Examples:
  >>> from pyhealth.datasets import MIMIC3Dataset
  >>> mimic3_ds = MIMIC3Dataset(
  ... root="/srv/local/data/physionet.org/files/mimiciii/1.4",
@@ -80,25 +69,19 @@ def drug_recommendation_mimic3_fn(patient: Patient):
 
 
 def drug_recommendation_mimic4_fn(patient: 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).
 
- Process a single patient for the drug recommendation task.
-
  Args:
  patient: a Patient object
 
  Returns:
  samples: a list of samples, each sample is a dict with patient_id, visit_id,
  and other task-specific attributes as key
-
- Note that a patient may be converted to multiple samples, e.g., a patient with
- three visits may be converted to three samples ([visit 1], [visit 1, visit 2],
- [visit 1, visit 2, visit 3]). Patients can also be excluded from the task
- dataset by returning an empty list.
  
-  **Example:**
+ Examples:
  >>> from pyhealth.datasets import MIMIC4Dataset
  >>> mimic4_ds = MIMIC4Dataset(
  ... root="/srv/local/data/physionet.org/files/mimiciv/2.0/hosp",
@@ -153,25 +136,19 @@ def drug_recommendation_mimic4_fn(patient: Patient):
 
 
 def drug_recommendation_eicu_fn(patient: 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).
 
- Process a single patient for the drug recommendation task.
-
  Args:
  patient: a Patient object
 
  Returns:
  samples: a list of samples, each sample is a dict with patient_id, visit_id,
  and other task-specific attributes as key
-
- Note that a patient may be converted to multiple samples, e.g., a patient with
- three visits may be converted to three samples ([visit 1], [visit 1, visit 2],
- [visit 1, visit 2, visit 3]). Patients can also be excluded from the task
- dataset by returning an empty list.
  
-  **Example:**
+ Examples:
  >>> from pyhealth.datasets import eICUDataset
  >>> eicu_ds = eICUDataset(
  ... root="/srv/local/data/physionet.org/files/eicu-crd/2.0",
@@ -225,25 +202,19 @@ def drug_recommendation_eicu_fn(patient: Patient):
 
 
 def drug_recommendation_omop_fn(patient: 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).
 
- Process a single patient for the drug recommendation task.
-
  Args:
  patient: a Patient object
 
  Returns:
  samples: a list of samples, each sample is a dict with patient_id, visit_id,
  and other task-specific attributes as key
-
- Note that a patient may be converted to multiple samples, e.g., a patient with
- three visits may be converted to three samples ([visit 1], [visit 1, visit 2],
- [visit 1, visit 2, visit 3]). Patients can also be excluded from the task
- dataset by returning an empty list.
  
- **Examples:**
+ Examples:
  >>> from pyhealth.datasets import OMOPDataset
  >>> omop_ds = OMOPDataset(
  ... root="https://storage.googleapis.com/pyhealth/synpuf1k_omop_cdm_5.2.2",
@@ -256,7 +227,7 @@ def drug_recommendation_omop_fn(patient: Patient):
  [{'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']]}]
  
  """
- 
+
  samples = []
  for i in range(len(patient)):
  visit: Visit = patient[i]

pyhealth/tasks/length_of_stay_prediction.py

@@ -2,7 +2,7 @@
 
 
 def categorize_los(days: int):
- """Categorize length of stay into 10 categories.
+ """Categorizes length of stay into 10 categories.
 
  One for ICU stays shorter than a day, seven day-long categories for each day of
  the first week, one for stays of over one week but less than two,
@@ -29,13 +29,12 @@ def categorize_los(days: int):
 
 
 def length_of_stay_prediction_mimic3_fn(patient: Patient):
- """
+ """Processes a single patient for the length-of-stay prediction task.
+
  Length of stay prediction aims at predicting the length of stay (in days) of the
  current hospital visit based on the clinical information from the visit
  (e.g., conditions and procedures).
 
- Process a single patient for the length-of-stay prediction task.
-
  Args:
  patient: a Patient object.
 
@@ -45,7 +44,7 @@ def length_of_stay_prediction_mimic3_fn(patient: Patient):
 
  Note that we define the task as a multi-class classification task.
  
-  **Example:**
+ Examples:
  >>> from pyhealth.datasets import MIMIC3Dataset
  >>> mimic3_ds = MIMIC3Dataset(
  ... root="/srv/local/data/physionet.org/files/mimiciii/1.4",
@@ -88,13 +87,12 @@ def length_of_stay_prediction_mimic3_fn(patient: Patient):
 
 
 def length_of_stay_prediction_mimic4_fn(patient: Patient):
- """
+ """Processes a single patient for the length-of-stay prediction task.
+
  Length of stay prediction aims at predicting the length of stay (in days) of the
  current hospital visit based on the clinical information from the visit
  (e.g., conditions and procedures).
 
- Process a single patient for the length-of-stay prediction task.
-
  Args:
  patient: a Patient object.
 
@@ -104,7 +102,7 @@ def length_of_stay_prediction_mimic4_fn(patient: Patient):
 
  Note that we define the task as a multi-class classification task.
  
-  **Example:**
+ Examples:
  >>> from pyhealth.datasets import MIMIC4Dataset
  >>> mimic4_ds = MIMIC4Dataset(
  ... root="/srv/local/data/physionet.org/files/mimiciv/2.0/hosp",
@@ -148,13 +146,12 @@ def length_of_stay_prediction_mimic4_fn(patient: Patient):
 
 
 def length_of_stay_prediction_eicu_fn(patient: Patient):
- """
+ """Processes a single patient for the length-of-stay prediction task.
+
  Length of stay prediction aims at predicting the length of stay (in days) of the
  current hospital visit based on the clinical information from the visit
  (e.g., conditions and procedures).
 
- Process a single patient for the length-of-stay prediction task.
-
  Args:
  patient: a Patient object.
 
@@ -164,7 +161,7 @@ def length_of_stay_prediction_eicu_fn(patient: Patient):
 
  Note that we define the task as a multi-class classification task.
  
-  **Example:**
+ Examples:
  >>> from pyhealth.datasets import eICUDataset
  >>> eicu_ds = eICUDataset(
  ... root="/srv/local/data/physionet.org/files/eicu-crd/2.0",
@@ -209,13 +206,12 @@ def length_of_stay_prediction_eicu_fn(patient: Patient):
 
 
 def length_of_stay_prediction_omop_fn(patient: Patient):
- """
+ """Processes a single patient for the length-of-stay prediction task.
+
  Length of stay prediction aims at predicting the length of stay (in days) of the
  current hospital visit based on the clinical information from the visit
  (e.g., conditions and procedures).
 
- Process a single patient for the length-of-stay prediction task.
-
  Args:
  patient: a Patient object.
 
@@ -225,7 +221,7 @@ def length_of_stay_prediction_omop_fn(patient: Patient):
 
  Note that we define the task as a multi-class classification task.
  
- **Examples:**
+ Examples:
  >>> from pyhealth.datasets import OMOPDataset
  >>> omop_ds = OMOPDataset(
  ... root="https://storage.googleapis.com/pyhealth/synpuf1k_omop_cdm_5.2.2",

pyhealth/tasks/mortality_prediction.py

@@ -1,18 +1,13 @@
-import sys
-
-# TODO: remove this hack later
-sys.path.append("/home/chaoqiy2/github/PyHealth-OMOP")
 from pyhealth.data import Patient, Visit
 
 
 def mortality_prediction_mimic3_fn(patient: Patient):
- """
+ """Processes a single patient for the mortality prediction task.
+
  Mortality prediction aims at predicting whether the patient will decease in the
  next hospital visit based on the clinical information from current visit
  (e.g., conditions and procedures).
 
- Process a single patient for the mortality prediction task.
-
  Args:
  patient: a Patient object
 
@@ -22,7 +17,7 @@ def mortality_prediction_mimic3_fn(patient: Patient):
 
  Note that we define the task as a binary classification task.
  
-  **Example:**
+ Examples:
  >>> from pyhealth.datasets import MIMIC3Dataset
  >>> mimic3_ds = MIMIC3Dataset(
  ... root="/srv/local/data/physionet.org/files/mimiciii/1.4",
@@ -69,13 +64,12 @@ def mortality_prediction_mimic3_fn(patient: Patient):
 
 
 def mortality_prediction_mimic4_fn(patient: Patient):
- """
+ """Processes a single patient for the mortality prediction task.
+
  Mortality prediction aims at predicting whether the patient will decease in the
  next hospital visit based on the clinical information from current visit
  (e.g., conditions and procedures).
 
- Process a single patient for the mortality prediction task.
-
  Args:
  patient: a Patient object
 
@@ -85,7 +79,7 @@ def mortality_prediction_mimic4_fn(patient: Patient):
 
  Note that we define the task as a binary classification task.
  
-  **Example:**
+ Examples:
  >>> from pyhealth.datasets import MIMIC4Dataset
  >>> mimic4_ds = MIMIC4Dataset(
  ... root="/srv/local/data/physionet.org/files/mimiciv/2.0/hosp",
@@ -132,13 +126,12 @@ def mortality_prediction_mimic4_fn(patient: Patient):
 
 
 def mortality_prediction_eicu_fn(patient: Patient):
- """
+ """Processes a single patient for the mortality prediction task.
+
  Mortality prediction aims at predicting whether the patient will decease in the
  next hospital visit based on the clinical information from current visit
  (e.g., conditions and procedures).
 
- Process a single patient for the mortality prediction task.
-
  Args:
  patient: a Patient object
 
@@ -148,7 +141,7 @@ def mortality_prediction_eicu_fn(patient: Patient):
 
  Note that we define the task as a binary classification task.
  
-  **Example:**
+ Examples:
  >>> from pyhealth.datasets import eICUDataset
  >>> eicu_ds = eICUDataset(
  ... root="/srv/local/data/physionet.org/files/eicu-crd/2.0",
@@ -195,13 +188,12 @@ def mortality_prediction_eicu_fn(patient: Patient):
 
 
 def mortality_prediction_omop_fn(patient: Patient):
- """
+ """Processes a single patient for the mortality prediction task.
+
  Mortality prediction aims at predicting whether the patient will decease in the
  next hospital visit based on the clinical information from current visit
  (e.g., conditions and procedures).
 
- Process a single patient for the mortality prediction task.
-
  Args:
  patient: a Patient object
 
@@ -211,7 +203,7 @@ def mortality_prediction_omop_fn(patient: Patient):
 
  Note that we define the task as a binary classification task.
  
- **Examples:**
+ Examples:
  >>> from pyhealth.datasets import OMOPDataset
  >>> omop_ds = OMOPDataset(
  ... root="https://storage.googleapis.com/pyhealth/synpuf1k_omop_cdm_5.2.2",
@@ -304,4 +296,3 @@ def mortality_prediction_omop_fn(patient: Patient):
  dataset.set_task(task_fn=mortality_prediction_omop_fn)
  dataset.stat()
  print(dataset.available_keys)
-