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Simulator

Simulator Overview

The simulator code is located in the Tools git repository, specifically under the MR_TOOLS repo at: AlgoMarker_python_API/PopulationAnalyzer.

Slides:

Running the Server

To start the server, execute ./ui.py from this directory, or use the full path to ui.py. The server default port is 3764.

Adding a New AlgoMarker

To add an additional AlgoMarker, copy an existing model file (e.g., LungFlag.py) into the "algomarkers" folder within this project. The filename you choose will be used in the application with a .py extension. The keyword _SLASH_ in filenames will be displayed as / in the UI.

In the Python config file for the AlgoMarker, define the following fields:

  • am_regions: Dictionary mapping region names (strings) to ReferenceInfo objects.
  • sample_per_pid: Numeric parameter for bootstrap assessment.
  • default_region: (Optional) String specifying the default region.
  • additional_info: String for descriptive text near the model selection.
  • optional_signals: (Optional) List of InputSignal objects describing input options (e.g., limiting history, selecting recent signals).
  • model_path: String specifying the model's path.
  • orderdinal: (Optional) Integer for ordering this AlgoMarker among others.

Example Configuration

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from models import *

lung_cohorts = [
    CohortInfo(cohort_name='Ever Smokers Age 50-80', bt_filter=lambda df: (df['age']>=50) & (df['age']<=80)),
    CohortInfo(cohort_name='Ever Smokers Age 45-80', bt_filter=lambda df: (df['age']>=45) & (df['age']<=80)),
    CohortInfo(cohort_name='Ever Smokers Age 40-90', bt_filter=lambda df: (df['age']>=40) & (df['age']<=90)),
    CohortInfo(cohort_name='Ever Smokers Age 55-74', bt_filter=lambda df: (df['age']>=55) & (df['age']<=74)),
]

us_lung_cohorts = [
    CohortInfo(cohort_name='Ever Smokers Age 50-80', bt_filter=lambda df: (df['age']>=50) & (df['age']<=80)),
    CohortInfo(cohort_name='Ever Smokers Age 55-74', bt_filter=lambda df: (df['age']>=55) & (df['age']<=74)),
    CohortInfo(cohort_name='Ever Smokers Age 45-90', bt_filter=lambda df: (df['age']>=45) & (df['age']<=90)),
    CohortInfo(
        cohort_name='USPSTF Age 50-80 (20 pack years, less then 15 years quit)',
        bt_filter=lambda df: (df['age']>=50) & (df['age']<=80) &
                             (df['smoking.smok_pack_years']>=20) &
                             (df['smoking.smok_days_since_quitting']<=15*365)
    ),
]

am_regions = {
    'US-KP': ReferenceInfo(
        matrix_path='/nas1/Work/Users/eitan/Lung/outputs/models2023/EX3/model_63/reference_matrices/reference_features_kp.final.matrix',
        control_weight=20,
        cohort_options=us_lung_cohorts,
        default_cohort='USPSTF Age 50-80 (20 pack years, less then 15 years quit)',
        repository_path='/nas1/Work/CancerData/Repositories/KP/kp.repository',
        model_cv_path='/nas1/Work/Users/eitan/Lung/outputs/models2023/EX3/model_63/results',
        model_cv_format='CV_MODEL_%d.medmdl'
    ),
    'UK-THIN': ReferenceInfo(
        matrix_path='/nas1/Work/Users/eitan/Lung/outputs/models2023/EX3/model_63/reference_matrices/reference_features_thin.final.matrix',
        cohort_options=lung_cohorts,
        default_cohort='Ever Smokers Age 55-74',
        repository_path='/nas1/Work/CancerData/Repositories/THIN/thin_2021.lung/thin.repository'
    ),
}

sample_per_pid = 0
default_region = 'UK-THIN'
additional_info = 'Time Window 90-365'

optional_signals = [
    InputSignalsExistence(
        signal_name='Smoking',
        list_raw_signals=['Smoking_Duration', 'Smoking_Intensity', 'Pack_Years', 'Smoking_Quit_Date'],
        tooltip_str='If true will include Smoking_Duration, Smoking_Intensity, Pack_Years, Smoking_Quit_Date in the inputs and not only status'
    ),
    InputSignalsExistence(
        signal_name='Labs',
        list_raw_signals=[
            "Albumin", "ALKP", "ALT", "Cholesterol", "Triglycerides", "LDL", "HDL", "Creatinine",
            "Glucose", "Urea", "Eosinophils%", "Hematocrit", "Hemoglobin", "MCHC-M", "MCH",
            "Neutrophils#", "Neutrophils%", "Platelets", "RBC", "WBC", "RDW", "Protein_Total",
            "Lymphocytes%", "Basophils%", "Monocytes%", "Lymphocytes#", "Basophils#", "Monocytes#",
            "Eosinophils#", "MCV"
        ]
    ),
    InputSignalsExistence(
        signal_name='BMI',
        list_raw_signals=['BMI', 'Weight', 'Height']
    ),
    InputSignalsExistence(
        signal_name='Spirometry',
        list_raw_signals=['Fev1']
    ),
]

model_path = '/earlysign/AlgoMarkers/LungFlag/lungflag.model'
orderdinal = 1