Improper pain management leads to severe physical or mental consequences, including suffering, a negative impact on quality of life, and an increased risk of opioid dependency. Assessing the presence and severity of pain is imperative to prevent such...
International journal of medical informatics
39003790
OBJECTIVE: To determine the incidence of patients presenting in pain to a large Australian inner-city emergency department (ED) using a clinical text deep learning algorithm.
BACKGROUND: Recent studies on machine learning have shown the potential to provide new methods with which to assess pain through the measurement of signals associated with physiologic responses to pain detected by wearables. We conducted a prospectiv...
Journal of cachexia, sarcopenia and muscle
39343707
BACKGROUND: Hip-related pain (HRP) affects young to middle-aged active adults and impacts physical activity, finances and quality of life. HRP includes conditions like femoroacetabular impingement syndrome and labral tears. Lateral hip muscle dysfunc...
Artificial intelligence (AI) and deep learning technologies hold promise for identifying effective drugs for human diseases, including pain. Here, we present an interpretable deep-learning-based ligand image- and receptor's three-dimensional (3D)-str...
Access to large amounts of data is essential for successful machine learning research. However, there is insufficient data for many applications, as data collection is often challenging and time-consuming. The same applies to automated pain recogniti...
Affective states are reflected in the facial expressions of all mammals. Facial behaviors linked to pain have attracted most of the attention so far in non-human animals, leading to the development of numerous instruments for evaluating pain through ...
: Assessing pain deception is challenging due to its subjective nature. The main goal of this study was to evaluate the diagnostic value of pain deception using machine learning (ML) analysis with the Minnesota Multiphasic Personality Inventory-2 (MM...
Currently, pain assessment using electroencephalogram signals and machine learning methods in clinical studies is of great importance, especially for those who cannot express their pain. Since newborns are among the high-risk group and always experie...
Advances in neonatal care : official journal of the National Association of Neonatal Nurses
39356566
BACKGROUND: Using Artificial Intelligence (AI) for neonatal pain assessment has great potential, but its effectiveness depends on accurate data labeling. Therefore, precise and reliable neonatal pain datasets are essential for managing neonatal pain.