AI Medical Compendium Journal:
JCO clinical cancer informatics

Showing 101 to 110 of 163 articles

Natural Language Processing for Patient Selection in Phase I or II Oncology Clinical Trials.

JCO clinical cancer informatics
PURPOSE: Early discontinuation affects more than one third of patients enrolled in early-phase oncology clinical trials. Early discontinuation is deleterious both for the patient and for the study, by inflating its duration and associated costs. We a...

Automated Identification of Patients With Immune-Related Adverse Events From Clinical Notes Using Word Embedding and Machine Learning.

JCO clinical cancer informatics
PURPOSE: Although immune checkpoint inhibitors (ICIs) have substantially improved survival in patients with advanced malignancies, they are associated with a unique spectrum of side effects termed immune-related adverse events (irAEs). To ensure trea...

Automated NLP Extraction of Clinical Rationale for Treatment Discontinuation in Breast Cancer.

JCO clinical cancer informatics
PURPOSE: Key oncology end points are not routinely encoded into electronic medical records (EMRs). We assessed whether natural language processing (NLP) can abstract treatment discontinuation rationale from unstructured EMR notes to estimate toxicity...

Natural Language Processing to Identify Cancer Treatments With Electronic Medical Records.

JCO clinical cancer informatics
PURPOSE: Knowing the treatments administered to patients with cancer is important for treatment planning and correlating treatment patterns with outcomes for personalized medicine study. However, existing methods to identify treatments are often lack...

Computing the Hazard Ratios Associated With Explanatory Variables Using Machine Learning Models of Survival Data.

JCO clinical cancer informatics
PURPOSE: The application of Cox proportional hazards (CoxPH) models to survival data and the derivation of hazard ratio (HR) are well established. Although nonlinear, tree-based machine learning (ML) models have been developed and applied to the surv...

External Validation of the Bone Metastases Ensemble Trees for Survival (BMETS) Machine Learning Model to Predict Survival in Patients With Symptomatic Bone Metastases.

JCO clinical cancer informatics
PURPOSE: The Bone Metastases Ensemble Trees for Survival (BMETS) model uses a machine learning algorithm to estimate survival time following consultation for palliative radiation therapy for symptomatic bone metastases (SBM). BMETS was developed at a...

Machine Learning Frameworks to Predict Neoadjuvant Chemotherapy Response in Breast Cancer Using Clinical and Pathological Features.

JCO clinical cancer informatics
PURPOSE: Neoadjuvant chemotherapy (NAC) is used to treat locally advanced breast cancer (LABC) and high-risk early breast cancer (BC). Pathological complete response (pCR) has prognostic value depending on BC subtype. Rates of pCR, however, can be va...

Artificial Intelligence Clinical Evidence Engine for Automatic Identification, Prioritization, and Extraction of Relevant Clinical Oncology Research.

JCO clinical cancer informatics
PURPOSE: We developed a system to automate analysis of the clinical oncology scientific literature from bibliographic databases and match articles to specific patient cohorts to answer specific questions regarding the efficacy of a treatment. The app...

Chemotherapy Knowledge Base Management in the Era of Precision Oncology.

JCO clinical cancer informatics
Cancer medicine has grown increasingly complex in recent years with the advent of precision oncology and wide utilization of multidrug regimens. Representing this increasingly granular knowledge is a significant challenge. As users and managers of a ...

Reimagining T Staging Through Artificial Intelligence and Machine Learning Image Processing Approaches in Digital Pathology.

JCO clinical cancer informatics
Tumor stage and grade, visually assessed by pathologists from evaluation of pathology images in conjunction with radiographic imaging techniques, have been linked to outcome, progression, and survival for a number of cancers. The gold standard of sta...