Machine Learning-Based Mortality Prediction Model for Critically Ill Cancer Patients Admitted to the Intensive Care Unit (CanICU).
Ryoung-Eun KoJaehyeong ChoMin-Kyue ShinSung Woo OhYeonchan SeongJeongseok JeonKyeongman JeonSoonmyung PaikJoon Seok LimSang Joon ShinJoong Bae AhnJong Hyuck ParkSeng Chan YouHan Sang KimPublished in: Cancers (2023)
CanICU offers improved performance for predicting mortality in critically ill cancer patients admitted to ICU. A user-friendly online implementation is available and should be valuable for better mortality risk stratification to allocate ICU care for cancer patients.
Keyphrases
- papillary thyroid
- cardiovascular events
- machine learning
- healthcare
- intensive care unit
- squamous cell
- risk factors
- primary care
- palliative care
- quality improvement
- mechanical ventilation
- social media
- type diabetes
- coronary artery disease
- lymph node metastasis
- cardiovascular disease
- childhood cancer
- acute respiratory distress syndrome
- health insurance