**Purpose:** Severe and febrile neutropenia present serious hazards to cancer patients undergoing chemotherapy. We seek to develop a machine learning-based neutropenia prediction model that can be used to assess risk at the initiation of a …
The COVID-19 pandemic has prompted an international effort to develop and repurpose medications and procedures to effectively combat the disease. Several groups have focused on the potential treatment utility of angiotensin-converting-enzyme …
The COVID-19 pandemic has created unprecedented challenges worldwide. Strained healthcare providers make difficult decisions on patient triage, treatment and care management on a daily basis. Policy makers have imposed social distancing measures to …
**Background:** Timely identification of COVID-19 patients at high risk of mortality can significantly improve patient management and resource allocation within hospitals. This study seeks to develop and validate a data-driven personalized mortality …
**Key objective:** To provide an overview of machine learning in oncology, both from a methods and applications perspective, and to offer a framework for leveraging machine learning in clinical decision making. **Knowledge generated:** This review …
State-of-the-art clustering algorithms use heuristics to partition the feature space and provide little insight into the rationale for cluster membership, limiting their interpretability. In healthcare applications, the latter poses a barrier to the …