Predicting In-Hospital Mortality After Acute Myeloid Leukemia Therapy: Through Supervised Machine Learning Algorithms.
Nauman S SiddiquiAndreas K KleinAmandeep GodaraRachel J BuchsbaumMichael C HughesPublished in: JCO clinical cancer informatics (2022)
Using readily accessible variables, inpatient mortality of patients on track for chemotherapy to treat AML can be predicted through ML algorithms. The model also predicted inpatient mortality when tested on different data representations and paves the way for future research.
Keyphrases
- machine learning
- acute myeloid leukemia
- big data
- end stage renal disease
- artificial intelligence
- deep learning
- cardiovascular events
- mental health
- palliative care
- ejection fraction
- chronic kidney disease
- newly diagnosed
- risk factors
- allogeneic hematopoietic stem cell transplantation
- peritoneal dialysis
- type diabetes
- working memory
- acute care
- stem cells
- locally advanced
- squamous cell carcinoma
- electronic health record
- cell therapy
- data analysis