Prediction of Prolonged Length of Hospital Stay After Cancer Surgery Using Machine Learning on Electronic Health Records: Retrospective Cross-sectional Study.
Yong-Yeon JoJai Hong HanHyun Woo ParkHyojung JungJae Dong LeeJipmin JungHyo Soung ChaDae Kyung SohnYul HwangboPublished in: JMIR medical informatics (2021)
A machine learning approach using EHRs may improve the prediction of prolonged length of hospital stay after primary cancer surgery. This algorithm may help to provide a more effective allocation of medical resources in cancer surgery.
Keyphrases
- papillary thyroid
- machine learning
- minimally invasive
- coronary artery bypass
- electronic health record
- healthcare
- squamous cell
- adverse drug
- surgical site infection
- emergency department
- lymph node metastasis
- artificial intelligence
- cross sectional
- coronary artery disease
- acute care
- big data
- percutaneous coronary intervention