Published on in Vol 12 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/49138, first published .
A Patient Similarity Network (CHDmap) to Predict Outcomes After Congenital Heart Surgery: Development and Validation Study

A Patient Similarity Network (CHDmap) to Predict Outcomes After Congenital Heart Surgery: Development and Validation Study

A Patient Similarity Network (CHDmap) to Predict Outcomes After Congenital Heart Surgery: Development and Validation Study

Journals

  1. Van den Eynde J. CHDmap: One Step Further Toward Integrating Medicine-Based Evidence Into Practice. JMIR Medical Informatics 2024;12:e52343 View
  2. Manuilova I, Bossenz J, Weise A, Boehm D, Strantz C, Unberath P, Reimer N, Metzger P, Pauli T, Werle S, Schulze S, Hiemer S, Ustjanzew A, Kestler H, Busch H, Brors B, Christoph J. Identifications of Similarity Metrics for Patients With Cancer: Protocol for a Scoping Review. JMIR Research Protocols 2024;13:e58705 View
  3. Kenig N, Monton Echeverria J, Muntaner Vives A. Artificial Intelligence in Surgery: A Systematic Review of Use and Validation. Journal of Clinical Medicine 2024;13(23):7108 View
  4. Mohammadi I, Rajai Firouzabadi S, Hosseinpour M, Akhlaghpasand M, Hajikarimloo B, Zeraatian-Nejad S, Sardari Nia P. Using artificial intelligence to predict post-operative outcomes in congenital heart surgeries: a systematic review. BMC Cardiovascular Disorders 2024;24(1) View