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This study demonstrates how TOPSIS, a multi-criteria decision-making method, effectively ranks hospital responses to the seven most prevalent cancer types in southwestern Mexico. Artificial intelligence supports the evaluation of criteria such as clinic availability, early detection, staff training, infrastructure, rural coverage, prevention, vaccination, multidisciplinary treatment, and palliative care. Results show that TOPSIS provides healthcare professionals with a practical tool for comparing hospital performance, underscoring the value of multicriteria methods in medical decision-making.

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Evaluation of Hospital Response to Various Types of Cancer in Southwestern Mexico Using TOPSIS Multi-Criteria Analysis

  • 会议论文

  • 发表日期：

    2026年

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  • Jesús Alberto Palma-García,
  • Alberto Ochoa-Zezzati,
  • Iván Gallardo-Bernal,
  • Fredy Omar Beltrán-Anaya

摘要

This study demonstrates how TOPSIS, a multi-criteria decision-making method, effectively ranks hospital responses to the seven most prevalent cancer types in southwestern Mexico. Artificial intelligence supports the evaluation of criteria such as clinic availability, early detection, staff training, infrastructure, rural coverage, prevention, vaccination, multidisciplinary treatment, and palliative care. Results show that TOPSIS provides healthcare professionals with a practical tool for comparing hospital performance, underscoring the value of multicriteria methods in medical decision-making.