AI Medical Compendium Journal:
Journal of pain and symptom management

Showing 11 to 16 of 16 articles

Identification of Uncontrolled Symptoms in Cancer Patients Using Natural Language Processing.

Journal of pain and symptom management
CONTEXT: For patients with cancer, uncontrolled pain and other symptoms are the leading cause of unplanned hospitalizations. Early access to specialty palliative care (PC) is effective to reduce symptom burden, but more efficient approaches are neede...

Natural Language Processing to Identify Advance Care Planning Documentation in a Multisite Pragmatic Clinical Trial.

Journal of pain and symptom management
CONTEXT: Large multisite clinical trials studying decision-making when facing serious illness require an efficient method for abstraction of advance care planning (ACP) documentation from clinical text documents. However, the current gold standard me...

Identifying Goals of Care Conversations in the Electronic Health Record Using Natural Language Processing and Machine Learning.

Journal of pain and symptom management
CONTEXT: Goals-of-care discussions are an important quality metric in palliative care. However, goals-of-care discussions are often documented as free text in diverse locations. It is difficult to identify these discussions in the electronic health r...

Comparing an Artificial Neural Network to Logistic Regression for Predicting ED Visit Risk Among Patients With Cancer: A Population-Based Cohort Study.

Journal of pain and symptom management
CONTEXT: Prior work using symptom burden to predict emergency department (ED) visits among patients with cancer has used traditional statistical methods such as logistic regression (LR). Machine learning approaches for prediction, such as artificial ...

Deep Natural Language Processing Identifies Variation in Care Preference Documentation.

Journal of pain and symptom management
CONTEXT: Documentation of care preferences within 48 hours of admission to an intensive care unit (ICU) is a National Quality Forum-endorsed quality metric for older adults. Care preferences are poorly captured by administrative data.

Machine Learning Methods to Extract Documentation of Breast Cancer Symptoms From Electronic Health Records.

Journal of pain and symptom management
CONTEXT: Clinicians document cancer patients' symptoms in free-text format within electronic health record visit notes. Although symptoms are critically important to quality of life and often herald clinical status changes, computational methods to a...