Identification of complications requiring interventions after gastrointestinal cancer surgery from real-world data: An external validation study.
Hiromitsu KinoshitaTatsuto NishigoriSusumu KunisawaKoya HidaHisahiro HosogiSusumu InamotoHiroaki HataRyo MatsusueYuichi ImanakaKazutaka ObamaYumi MatsumuraPublished in: Annals of gastroenterological surgery (2023)
Patients undergoing GI cancer surgery and postoperative complications requiring interventions can be accurately identified using the real-world data. This multicenter external validation study may contribute to future research on hospital quality improvement or to a large-scale comparison study among nationwide hospitals using real-world data.
Keyphrases
- papillary thyroid
- minimally invasive
- electronic health record
- patients undergoing
- quality improvement
- big data
- coronary artery bypass
- healthcare
- physical activity
- squamous cell
- cross sectional
- risk factors
- machine learning
- emergency department
- squamous cell carcinoma
- coronary artery disease
- current status
- young adults
- atrial fibrillation
- double blind
- deep learning
- acute care