Utilization of Machine Learning to Model Important Features of 30-day Readmissions following Surgery for Metastatic Spinal Column Tumors: The Influence of Frailty.
Aladine A ElsamadicyAndrew B KooBenjamin C ReevesJames L CrossAndrew M HershAstrid C HengartnerAditya V KarhadeZach PenningtonOluwaseun O AkinduroSheng-Fu Larry LoZiya L GokaslanJohn H ShinEhud MendelDaniel M SciubbaPublished in: Global spine journal (2022)
Our study utilizes machine learning approaches and predictive modeling to identify frailty as a significant risk-factor that contributes to unplanned 30-day readmission after spine surgery for metastatic spinal column metastases.
Keyphrases
- machine learning
- squamous cell carcinoma
- small cell lung cancer
- spinal cord
- minimally invasive
- artificial intelligence
- liquid chromatography
- risk factors
- big data
- coronary artery bypass
- deep learning
- mass spectrometry
- acute coronary syndrome
- high resolution
- coronary artery disease
- atrial fibrillation
- surgical site infection
- simultaneous determination