Pain Management

Deep Learning Algorithm Trained on Lumbar Magnetic Resonance Imaging to Predict Outcomes of Transforaminal Epidural Steroid Injection for Chronic Lumbosacral Radicular Pain.

BACKGROUND: Transforaminal epidural steroid injections (TFESI) are widely used to alleviate lumbosacral radicular pain. Knowledge of the therapeutic outcomes of TFESI allows clinicians to elucidate therapeutic plans for managing lumbosacral radicular pain. Deep learning (DL) can outperform traditional machine learning techniques and learn from unstructured and perceptual data. A convolutional neur...

ATLAS: An Adaptive Transfer Learning Based Pain Assessment System: A Real Life Unsupervised Pain Assessment Solution.

Undertreatment or overtreatment of pain will cause severe consequences physiologically and psychologically. Thus, researchers have made great efforts to develop automatic pain assessment approaches based on physiological signals using machine learning techniques. However, state-of-art research mainly focuses on verifying the hypothesis that physiological signals can be used to assess pain. The cri...

Convolution Neural Network for Pain Intensity Assessment from Facial Expression.

Pain is an unpleasant feeling that can reflect a patient's health situation. Since measuring pain is subjective, time-consuming, and needs continuous ...

Using Natural Language Processing of Clinical Notes to Predict Outcomes of Opioid Treatment Program.

Potential of natural language processing (NLP) in extracting patient's information from clinical notes of opioid treatment programs (OTP) and leveragi...

Classification of Tonic Pain Experience based on Phase Connectivity in the Alpha Frequency Band of the Electroencephalogram using Convolutional Neural Networks.

The complexity of brain activity involved in the generation of the experience of pain makes it hard to identify neural markers able to predict pain st...

Care Models for Acute Chest Pain That Improve Outcomes and Efficiency: JACC State-of-the-Art Review.

Existing assessment pathways for acute chest pain are often resource-intensive, prolonged, and expensive. In this review, the authors describe existin...

Artificial intelligence in neuropathology: Current status and future perspectives.

Machine learning and artificial intelligence (AI) have become a part of our daily routine. There are very few of us who are not influenced by this tec...

Editorial Commentary: Big Data and Machine Learning in Medicine.

Recent research using machine learning and data mining to determine predictors of prolonged opioid use after arthroscopic surgery showed that Artifici...

The Analysis of Pain Research through the Lens of Artificial Intelligence and Machine Learning.

BACKGROUND: Traditional pain assessment methods have significant limitations due to the high variability in patient reported pain scores and perceptio...

Advances in Deep Neuropathological Phenotyping of Alzheimer Disease: Past, Present, and Future.

Alzheimer disease (AD) is a neurodegenerative disorder characterized pathologically by the presence of neurofibrillary tangles and amyloid beta (Aβ) p...

Shedding light on pain for the clinic: a comprehensive review of using functional near-infrared spectroscopy to monitor its process in the brain.

Pain is a complex experience that involves sensation, emotion, and cognition. The subjectivity of the traditional pain measurement tools has expedited...

Bias and fairness assessment of a natural language processing opioid misuse classifier: detection and mitigation of electronic health record data disadvantages across racial subgroups.

OBJECTIVES: To assess fairness and bias of a previously validated machine learning opioid misuse classifier.

Comment on: "Predictive factors for opioid-free management after robotic radical prostatectomy: the value of a single-port robotic platform".

Disentangling data dependency using cross-validation strategies to evaluate prediction quality of cattle grazing activities using machine learning algorithms and wearable sensor data.

Wearable sensors have been explored as an alternative for real-time monitoring of cattle feeding behavior in grazing systems. To evaluate the performa...

Detection of Optic Disc Abnormalities in Color Fundus Photographs Using Deep Learning.

BACKGROUND: To date, deep learning-based detection of optic disc abnormalities in color fundus photographs has mostly been limited to the field of gla...

Extraperitoneal Single-Port Robot-Assisted Radical Prostatectomy.

Robot-assisted radical prostatectomy (RARP) is currently the standard minimally invasive procedure for the surgical management of localized prostate c...

Application of bi-modal signal in the classification and recognition of drug addiction degree based on machine learning.

Most studies on drug addiction degree are made based on statistical scales, addicts' account, and subjective judgement of rehabilitation doctors. No o...

Prediction of Prolonged Opioid Use After Surgery in Adolescents: Insights From Machine Learning.

BACKGROUND: Long-term opioid use has negative health care consequences. Patients who undergo surgery are at risk for prolonged opioid use after surger...

Identifying risk of opioid use disorder for patients taking opioid medications with deep learning.

OBJECTIVE: The United States is experiencing an opioid epidemic. In recent years, there were more than 10 million opioid misusers aged 12 years or old...

Clinical Performance of a Gene-Based Machine Learning Classifier in Assessing Risk of Developing OUD in Subjects Taking Oral Opioids: A Prospective Observational Study.

OBJECTIVE: To reduce the incidence of Opioid Use Disorder (OUD), multiple guidelines recommend assessing the risk of OUD prior to prescribing oral opi...