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Real-Time Classification of Causes of Death Using AI: Sensitivity Analysis.

Patrícia Pita FerreiraDiogo Godinho SimõesConstança Pinto de CarvalhoFrancisco DuarteEugénia FernandesPedro CasacaJosé Francisco LoffAna Paula SoaresMaria João AlbuquerquePedro Pinto LeiteAndré Peralta-Santos
Published in: JMIR AI (2023)
Our findings indicate that, during periods of excess and extreme excess mortality, AUTOCOD's performance remains unaffected by potential text quality degradation because of pressure on health services. Consequently, AUTOCOD can be dependably used for real-time cause-specific mortality surveillance even in extreme excess mortality situations.
Keyphrases
  • cardiovascular events
  • risk factors
  • climate change
  • machine learning
  • public health
  • type diabetes
  • coronary artery disease
  • quality improvement