Machine Learning-Based Exploratory Clinical Decision Support for Newly Diagnosed Patients With Acute Myeloid Leukemia Treated With 7 + 3 Type Chemotherapy or Venetoclax/Azacitidine.
Nazmul IslamJamie S ReubenJustin DaleJon GutmanChristine M McMahonMaria AmayaBruce GoodmanJoseph ToninatoMaura GasparettoBrett StevensShanshan PeiAustin GillenSarah StaggsKrysta EngelSarah DavisMadelyne HullElizabeth BurkeLenny LarchickRichard ZaneGrant WellerCraig T JordanClayton A SmithPublished in: JCO clinical cancer informatics (2022)
Potential ML-based approaches to clinical decision support to help guide individual patients with newly diagnosed AML to either 7 + 3 or venetoclax plus azacitidine induction therapy were identified. Larger cohorts with separate test and validation studies are necessary to confirm these initial findings.
Keyphrases
- clinical decision support
- acute myeloid leukemia
- newly diagnosed
- machine learning
- electronic health record
- chronic lymphocytic leukemia
- allogeneic hematopoietic stem cell transplantation
- artificial intelligence
- big data
- case control
- stem cells
- human health
- squamous cell carcinoma
- risk assessment
- deep learning
- mesenchymal stem cells
- climate change
- cell therapy