AI Medical Compendium Journal:
Journal of pain and symptom management

Showing 1 to 10 of 16 articles

NLP for Analyzing Electronic Health Records and Clinical Notes in Cancer Research: A Review.

Journal of pain and symptom management
This review examines the application of natural language processing (NLP) techniques in cancer research using electronic health records (EHRs) and clinical notes. It addresses gaps in existing literature by providing a broader perspective than previo...

Large Language Models to Identify Advance Care Planning in Patients With Advanced Cancer.

Journal of pain and symptom management
CONTEXT: Efficiently tracking Advance Care Planning (ACP) documentation in electronic heath records (EHRs) is essential for quality improvement and research efforts. The use of large language models (LLMs) offers a novel approach to this task.

Machine Learning for Targeted Advance Care Planning in Cancer Patients: A Quality Improvement Study.

Journal of pain and symptom management
CONTEXT: Prognostication challenges contribute to delays in advance care planning (ACP) for patients with cancer near the end of life (EOL).

Artificial Intelligence and Machine Learning in Cancer Pain: A Systematic Review.

Journal of pain and symptom management
BACKGROUND/OBJECTIVES: Pain is a challenging multifaceted symptom reported by most cancer patients. This systematic review aims to explore applications of artificial intelligence/machine learning (AI/ML) in predicting pain-related outcomes and pain m...

AI-Generated Content in Cancer Symptom Management: A Comparative Analysis Between ChatGPT and NCCN.

Journal of pain and symptom management
BACKGROUND: Artificial intelligence-driven tools, like ChatGPT, are prevalent sources for online health information. Limited research has explored the congruity between AI-generated content and professional treatment guidelines. This study seeks to c...

Effect of an Artificial Intelligence Decision Support Tool on Palliative Care Referral in Hospitalized Patients: A Randomized Clinical Trial.

Journal of pain and symptom management
CONTEXT: Palliative care services are commonly provided to hospitalized patients, but accurately predicting who needs them remains a challenge.

Mixed-methods evaluation of three natural language processing modeling approaches for measuring documented goals-of-care discussions in the electronic health record.

Journal of pain and symptom management
CONTEXT: Documented goals-of-care discussions are an important quality metric for patients with serious illness. Natural language processing (NLP) is a promising approach for identifying goals-of-care discussions in the electronic health record (EHR)...

Palliative Care Exposure Relative to Predicted Risk of Six-Month Mortality in Hospitalized Adults.

Journal of pain and symptom management
CONTEXT: The optimal strategy for implementing mortality-predicting algorithms to facilitate clinical care, prognostic discussions, and palliative care interventions remains unknown.

A Comparison of Models Predicting One-Year Mortality at Time of Admission.

Journal of pain and symptom management
CONTEXT: Hospitalization provides an opportunity to address end-of-life care (EoLC) preferences if patients at risk of death can be accurately identified while in the hospital. The modified Hospital One-Year Mortality Risk (mHOMR) uses demographic an...