Personalized decision making for coronary artery disease treatment using offline reinforcement learning

Related articles

1. IMPROVE Decision Rule for Carotid Revascularization: Clinician Perspectives on Acceptability and Implementation Barriers

   This article has 12 authors:

   1. Juul Bierens
   2. Stephanie Ament
   3. Martine Truijman
   4. Gert J. de Borst
   5. Paul Nederkoorn
   6. Daniel Bos
   7. Manuela Joore
   8. Alida Postma
   9. Eline Kooi
   10. Robert van Oostenbrugge
   11. Luc Smits
   12. on behalf of the IMPROVE Investigators

2. Model-based cost-effectiveness of the IMPROVE score versus care as usual for risk-based selection of symptomatic patients for carotid revascularization

   This article has 13 authors:

   1. Kelly Nies
   2. Bram Ramaekers
   3. Dorothee Auer
   4. Andreas Schindler
   5. Tobias Saam
   6. Daniel Bos
   7. Pim de Jong
   8. Paul Nederkoorn
   9. Gert J. de Borst
   10. Robert van Oostenbrugge
   11. Manuela Joore
   12. M. Eline Kooi
   13. Luc Smits

3. Machine learning models for predicting medium-term heart failure prognosis: Discrimination and calibration analyses

   This article has 16 authors:

   1. Takuya Nishino
   2. Katsuhito Kato
   3. Shuhei Tara
   4. Daisuke Hayashi
   5. Tomohisa Seki
   6. Toru Takiguchi
   7. Yoshiaki Kubota
   8. Takeshi Yamamoto
   9. Mitsunori Maruyama
   10. Eitaro Kodani
   11. Nobuaki Kobayashi
   12. Akihiro Shirakabe
   13. Toshiaki Otsuka
   14. Shoji Yokobori
   15. Yukihiro Kondo
   16. Kuniya Asai