138 lines
5.3 KiB
Python
138 lines
5.3 KiB
Python
from __future__ import annotations
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import csv
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import re
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from pathlib import Path
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LABELS = Path("labels.csv")
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OUT = Path("icd10_organ_label_mapping.csv")
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ICD10_CHAPTERS = [
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("A00", "B99", "I", "Certain infectious and parasitic diseases", "infection_immune"),
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("C00", "D48", "II", "Neoplasms", "neoplasm"),
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("D50", "D89", "III", "Diseases of the blood and immune mechanism", "hematologic_immune"),
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("E00", "E90", "IV", "Endocrine, nutritional and metabolic diseases", "metabolic_endocrine"),
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("F00", "F99", "V", "Mental and behavioural disorders", "mental_behavioral"),
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("G00", "G99", "VI", "Diseases of the nervous system", "neurologic"),
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("H00", "H59", "VII", "Diseases of the eye and adnexa", "sensory_eye"),
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("H60", "H95", "VIII", "Diseases of the ear and mastoid process", "sensory_ear"),
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("I00", "I99", "IX", "Diseases of the circulatory system", "cardiovascular"),
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("J00", "J99", "X", "Diseases of the respiratory system", "respiratory"),
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("K00", "K93", "XI", "Diseases of the digestive system", "digestive_liver"),
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("L00", "L99", "XII", "Diseases of the skin and subcutaneous tissue", "skin_soft_tissue"),
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("M00", "M99", "XIII", "Diseases of the musculoskeletal system", "musculoskeletal"),
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("N00", "N99", "XIV", "Diseases of the genitourinary system", "genitourinary_renal"),
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("O00", "O99", "XV", "Pregnancy, childbirth and puerperium", "pregnancy_reproductive"),
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("P00", "P96", "XVI", "Certain conditions originating in the perinatal period", "perinatal"),
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("Q00", "Q99", "XVII", "Congenital malformations", "congenital"),
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("R00", "R99", "XVIII", "Symptoms, signs and abnormal findings", "symptoms_findings"),
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("S00", "T98", "XIX", "Injury, poisoning and external causes", "injury_poisoning"),
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("V01", "Y98", "XX", "External causes of morbidity and mortality", "external_causes"),
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("Z00", "Z99", "XXI", "Factors influencing health status", "health_status_factors"),
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("U00", "U99", "XXII", "Codes for special purposes", "special_purpose"),
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]
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ORGAN_OVERRIDES = [
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("I60", "I69", "brain_vascular"),
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("N17", "N19", "kidney"),
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("K70", "K77", "liver"),
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("E10", "E14", "diabetes_metabolic"),
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("F00", "F09", "cognition_neuropsychiatric"),
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("G30", "G32", "cognition_neurodegenerative"),
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("H53", "H54", "sensory_vision"),
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("H90", "H91", "sensory_hearing"),
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("J40", "J47", "chronic_respiratory"),
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("C00", "D48", "neoplasm"),
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]
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def _code_key(code: str) -> tuple[str, int, str]:
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code = code.strip().upper()
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match = re.match(r"^([A-Z])(\d{2})(?:\.?([A-Z0-9]+))?", code)
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if not match:
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raise ValueError(f"Invalid ICD-10 code: {code!r}")
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letter, number, suffix = match.groups()
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return letter, int(number), suffix or ""
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def _code_in_range(code: str, start: str, end: str) -> bool:
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c_letter, c_num, _ = _code_key(code)
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s_letter, s_num, _ = _code_key(start)
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e_letter, e_num, _ = _code_key(end)
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if s_letter == e_letter:
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return c_letter == s_letter and s_num <= c_num <= e_num
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return (s_letter < c_letter < e_letter) or (
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c_letter == s_letter and c_num >= s_num
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) or (c_letter == e_letter and c_num <= e_num)
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def _chapter_for_code(code: str) -> tuple[str, str, str]:
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if not re.match(r"^[A-Z]\d{2}", code.strip().upper()):
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return "", "", "unmapped"
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for start, end, chapter_id, chapter_name, default_system in ICD10_CHAPTERS:
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if _code_in_range(code, start, end):
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return chapter_id, chapter_name, default_system
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return "", "", "unmapped"
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def _organ_system_for_code(code: str, default_system: str) -> str:
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if default_system == "unmapped":
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return "unmapped"
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for start, end, organ_system in ORGAN_OVERRIDES:
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if _code_in_range(code, start, end):
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return organ_system
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return default_system
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def main() -> None:
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rows = []
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with LABELS.open(encoding="utf-8") as f:
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for i, line in enumerate(f):
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line = line.strip()
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if not line:
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continue
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parts = line.split(maxsplit=1)
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code = parts[0].strip().upper()
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name = parts[1].strip() if len(parts) > 1 else ""
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chapter_id, chapter_name, default_system = _chapter_for_code(code)
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organ_system = _organ_system_for_code(code, default_system)
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rows.append(
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{
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"token_id": i + 3,
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"label_code": code,
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"label_name": name,
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"icd10_chapter_id": chapter_id,
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"icd10_chapter_name": chapter_name,
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"organ_system": organ_system,
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"organ_weight": 1.0 if organ_system != "unmapped" else 0.0,
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"match_source": "icd10_chapter_range",
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}
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)
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fieldnames = [
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"token_id",
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"label_code",
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"label_name",
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"icd10_chapter_id",
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"icd10_chapter_name",
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"organ_system",
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"organ_weight",
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"match_source",
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]
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with OUT.open("w", newline="", encoding="utf-8-sig") as f:
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writer = csv.DictWriter(f, fieldnames=fieldnames)
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writer.writeheader()
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writer.writerows(rows)
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print(f"labels: {len(rows)}")
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print(f"output: {OUT}")
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systems = sorted({row["organ_system"] for row in rows})
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print("organ_systems:", ", ".join(systems))
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if __name__ == "__main__":
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main()
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