{
  "experiment_name": "comorbidities_detection_multitask",
  "description": "Multi-task prediction of comorbidities and demographics from AbdCTBench",

  "binary_biomarkers": [
    {"name": "MORTALITY",   "description": "Death in the followup period", "positive_class": "PRESENT"},
    {"name": "HCC12",       "description": "HCC code 12 — Breast, Prostate, and other cancers", "positive_class": "PRESENT"},
    {"name": "HCC18",       "description": "HCC code 18 — Diabetes with Chronic Complications", "positive_class": "PRESENT"},
    {"name": "HCC96",       "description": "HCC code 96 — Cardiac arrhythmias", "positive_class": "PRESENT"},
    {"name": "HCC108",      "description": "HCC code 108 — Vascular disease", "positive_class": "PRESENT"},
    {"name": "HCC111",      "description": "HCC code 111 — Chronic obstructive pulmonary disease", "positive_class": "PRESENT"},
    {"name": "T2D",         "description": "Type 2 Diabetes", "positive_class": "PRESENT"},
    {"name": "MI",          "description": "Myocardial Infarction", "positive_class": "PRESENT"},
    {"name": "CALCIUMSCORING_ABDOMINALAGATSTON_BINARY", "description": "High abdominal aortic calcium score (Agatston > 1000)", "positive_class": "PRESENT"}
  ],

  "multiclass_biomarkers": [],

  "continuous_biomarkers": [
    {
      "name": "AGE",
      "description": "Patient age in years (min-max normalized to [0, 1] during training)",
      "min_value": 18,
      "max_value": 89,
      "normalization": "min_max"
    }
  ],

  "preprocessing": {
    "image_size": 256,
    "normalize_images": true,
    "convert_to_rgb": true
  },

  "training": {
    "class_weighting": true,
    "balanced_sampling": true
  },

  "validation": {
    "threshold_optimization": true,
    "optimization_metric": "f1_score",
    "per_biomarker_thresholds": true,
    "threshold_search_range": [0.1, 0.9],
    "threshold_search_steps": 9,
    "fallback_threshold": 0.5,
    "metrics": [
      "auroc",
      "accuracy",
      "sensitivity",
      "specificity",
      "f1_score",
      "precision",
      "recall"
    ],
    "regression_metrics": [
      "mse",
      "mae",
      "r2_score"
    ]
  }
}