Artificial Intelligence and Machine Learning in Cancer Related Pain: A Systematic Review.
Vivian SalamaBrandon GodinichYimin GengLaia Humbert-VidanLaura MauleKareem A WahidMohamed A NaserRenjie HeAbdallah Sherif Radwan MohamedClifton David FullerAmy C MorenoPublished in: medRxiv : the preprint server for health sciences (2023)
Implementation of various novel AI/ML tools promises significant advances in the classification, risk stratification, and management decisions for cancer pain. These advanced tools will integrate big health-related data for personalized pain management in cancer patients. Further research focusing on model calibration and rigorous external clinical validation in real healthcare settings is imperative for ensuring its practical and reliable application in clinical practice.
Keyphrases
- artificial intelligence
- pain management
- machine learning
- big data
- chronic pain
- healthcare
- deep learning
- clinical practice
- primary care
- papillary thyroid
- quality improvement
- electronic health record
- neuropathic pain
- spinal cord injury
- squamous cell carcinoma
- lymph node metastasis
- low cost
- childhood cancer
- affordable care act