Uncertainty quantification in neural-network based pain intensity estimation

B Ozek, Z Lu, S Radhakrishnan, S Kamarthi - arXiv preprint arXiv …, 2023 - arxiv.org
Improper pain management can lead to severe physical or mental consequences, including
suffering, and an increased risk of opioid dependency. Assessing the presence and severity …

Intelligent sight and sound: a chronic cancer pain dataset

C Ordun, AN Cha, E Raff, B Gaskin, A Hanson… - arXiv preprint arXiv …, 2022 - arxiv.org
Cancer patients experience high rates of chronic pain throughout the treatment process.
Assessing pain for this patient population is a vital component of psychological and …

[HTML][HTML] Predictors of sickness absence in a clinical population with chronic pain

R LoMartire, Ö Dahlström, M Björk, L Vixner… - The Journal of …, 2021 - Elsevier
Chronic pain-related sickness absence is an enormous socioeconomic burden globally.
Optimized interventions are reliant on a lucid understanding of the distribution of social …

Evidence-and data-driven classification of low back pain via artificial intelligence: Protocol of the PREDICT-LBP study

DL Belavy, SD Tagliaferri, M Tegenthoff… - Plos one, 2023 - journals.plos.org
In patients presenting with low back pain (LBP), once specific causes are excluded (fracture,
infection, inflammatory arthritis, cancer, cauda equina and radiculopathy) many clinicians …

Decoding pain from brain activity

ZS Chen - Journal of Neural Engineering, 2021 - iopscience.iop.org
Pain is a dynamic, complex and multidimensional experience. The identification of pain from
brain activity as neural readout may effectively provide a neural code for pain, and further …

[HTML][HTML] Cracking the Chronic Pain code: A scoping review of Artificial Intelligence in Chronic Pain research

MA Khan, RGL Koh, S Rashidiani, T Liu, V Tucci… - Artificial Intelligence in …, 2024 - Elsevier
Objective: The aim of this review is to identify gaps and provide a direction for future
research in the utilization of Artificial Intelligence (AI) in chronic pain (CP) management …

[HTML][HTML] Exploring the use of wearable sensors and natural language processing technology to improve patient-clinician communication: protocol for a feasibility study

V LeBaron, M Boukhechba, J Edwards… - JMIR Research …, 2022 - researchprotocols.org
Background: Effective communication is the bedrock of quality health care, but it continues to
be a major problem for patients, family caregivers, health care providers, and organizations …

Hyperparameter-tuned prediction of somatic symptom disorder using functional near-infrared spectroscopy-based dynamic functional connectivity

A Eken, B Çolak, NB Bal, A Kuşman… - Journal of neural …, 2019 - iopscience.iop.org
Objective. Somatic symptom disorder (SSD) is a reflection of medically unexplained physical
symptoms that lead to distress and impairment in social and occupational functioning. SSD …

Machine learning-based evaluation of spontaneous pain and analgesics from cellular calcium signals in the mouse primary somatosensory cortex using explainable …

MS Bak, H Park, H Yoon, G Chung, H Shin… - Frontiers in Molecular …, 2024 - frontiersin.org
Introduction Pain that arises spontaneously is considered more clinically relevant than pain
evoked by external stimuli. However, measuring spontaneous pain in animal models in …

Classification of elderly pain severity from automated video clip facial action unit analysis: A study from a Thai data repository

P Gomutbutra, A Kittisares, A Sanguansri… - Frontiers in Artificial …, 2022 - frontiersin.org
Data from 255 Thais with chronic pain were collected at Chiang Mai Medical School
Hospital. After the patients self-rated their level of pain, a smartphone camera was used to …