The Role of Autonomic Nervous System in Pain Chronicity DOI Creative Commons
Dmitry Kruglov, Dermot McGuckin

Physiology, Journal Year: 2023, Volume and Issue: unknown

Published: July 13, 2023

The role of the autonomic nervous system (ANS) in chronic pain (CP) and its chronicity is considered secondary reactive to nociceptive processes somatic (SomNS). However, research clinical data strongly suggest opposite. ANS an ancient, complex ample part system. It serves controls visceral organs tissues. takes all aspects types influences mechanisms at both peripheral central levels. In this chapter we bring together evidence from biomedical disciplines practice support alternative theory which contradicts traditional views on subject. We also raise questions require further consolidate facts, advance our knowledge improve treatment strategies for CP. importance topic difficult overestimate because significant impact CP society lack understanding, efficient therapy or cure.

Language: Английский

Enhancing mental health with Artificial Intelligence: Current trends and future prospects DOI Creative Commons
David B. Olawade, Ojima Z. Wada, Aderonke Odetayo

et al.

Journal of Medicine Surgery and Public Health, Journal Year: 2024, Volume and Issue: 3, P. 100099 - 100099

Published: April 17, 2024

Artificial Intelligence (AI) has emerged as a transformative force in various fields, and its application mental healthcare is no exception. Hence, this review explores the integration of AI into healthcare, elucidating current trends, ethical considerations, future directions dynamic field. This encompassed recent studies, examples applications, considerations shaping Additionally, regulatory frameworks trends research development were analyzed. We comprehensively searched four databases (PubMed, IEEE Xplore, PsycINFO, Google Scholar). The inclusion criteria papers published peer-reviewed journals, conference proceedings, or reputable online databases, that specifically focus on field offer comprehensive overview, analysis, existing literature English language. Current reveal AI's potential, with applications such early detection health disorders, personalized treatment plans, AI-driven virtual therapists. However, these advancements are accompanied by challenges concerning privacy, bias mitigation, preservation human element therapy. Future emphasize need for clear frameworks, transparent validation models, continuous efforts. Integrating therapy represents promising frontier healthcare. While holds potential to revolutionize responsible implementation essential. By addressing thoughtfully, we may effectively utilize enhance accessibility, efficacy, ethicality thereby helping both individuals communities.

Language: Английский

Citations

100

Application of AI in Multilevel Pain Assessment Using Facial Images: Systematic Review and Meta-Analysis DOI Creative Commons
Jian Zhong Huo, Yan Yu, Wei Lin

et al.

Journal of Medical Internet Research, Journal Year: 2024, Volume and Issue: 26, P. e51250 - e51250

Published: April 12, 2024

Background The continuous monitoring and recording of patients’ pain status is a major problem in current research on postoperative management. In the large number original or review articles focusing different approaches for assessment, many researchers have investigated how computer vision (CV) can help by capturing facial expressions. However, there lack proper comparison results between studies to identify gaps. Objective purpose this systematic meta-analysis was investigate diagnostic performance artificial intelligence models multilevel assessment from images. Methods PubMed, Embase, IEEE, Web Science, Cochrane Library databases were searched related publications before September 30, 2023. Studies that used images alone estimate multiple values included review. A study quality conducted using Quality Assessment Diagnostic Accuracy Studies, 2nd edition tool. these assessed metrics including sensitivity, specificity, log odds ratio (LDOR), area under curve (AUC). intermodal variability presented forest plots. Results total 45 reports reported test accuracies ranged 0.27-0.99, other metrics, mean standard error (MSE), absolute (MAE), intraclass correlation coefficient (ICC), Pearson (PCC), 0.31-4.61, 0.24-2.8, 0.19-0.83, 0.48-0.92, respectively. total, 6 meta-analysis. Their combined sensitivity 98% (95% CI 96%-99%), specificity 97%-99%), LDOR 7.99 6.73-9.31), AUC 0.99 0.99-1). subgroup analysis showed acceptable, although imbalanced data still emphasized as problem. All had at least one domain with high risk bias, 20% (9/45) studies, no applicability concerns. Conclusions This summarizes recent evidence automatic estimation expressions compared accuracy Promising established CV algorithms. Weaknesses also identified, suggesting larger evaluating multiclass classification could improve future studies. Trial Registration PROSPERO CRD42023418181; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=418181

Language: Английский

Citations

7

Voice EHR: introducing multimodal audio data for health DOI Creative Commons

James Anibal,

Hannah Huth, Ming Li

et al.

Frontiers in Digital Health, Journal Year: 2025, Volume and Issue: 6

Published: Jan. 28, 2025

Introduction Artificial intelligence (AI) models trained on audio data may have the potential to rapidly perform clinical tasks, enhancing medical decision-making and potentially improving outcomes through early detection. Existing technologies depend limited datasets collected with expensive recording equipment in high-income countries, which challenges deployment resource-constrained, high-volume settings where a profound impact health equity. Methods This report introduces novel protocol for collection corresponding application that captures information guided questions. Results To demonstrate of Voice EHR as biomarker health, initial experiments quality multiple case studies are presented this report. Large language (LLMs) were used compare transcribed (from same patients) conventional techniques like choice Information contained samples was consistently rated equally or more relevant evaluation. Discussion The HEAR facilitates an electronic record (“Voice EHR”) contain complex biomarkers from voice/respiratory features, speech patterns, spoken semantic meaning longitudinal context–potentially compensating typical limitations unimodal datasets.

Language: Английский

Citations

0

The Bridge2AI-voice application: initial feasibility study of voice data acquisition through mobile health DOI Creative Commons

Elijah Moothedan,

Micah Boyer, Stephanie Watts

et al.

Frontiers in Digital Health, Journal Year: 2025, Volume and Issue: 7

Published: April 15, 2025

Bridge2AI-Voice, a collaborative multi-institutional consortium, aims to generate large-scale, ethically sourced voice, speech, and cough database linked health metadata in order support AI-driven research. A novel smartphone application, the Bridge2AI-Voice app, was created collect standardized recordings of acoustic tasks, validated patient questionnaires, reported outcomes. Before broad data collection, feasibility study undertaken assess viability app clinical setting through task performance metrics participant feedback. Participants were recruited from tertiary academic voice center. instructed complete series tasks application on an iPad. The Plan-Do-Study-Act model for quality improvement implemented. Data collected included demographics including time completion, successful task/recording need assistance. Participant feedback measured by qualitative interview adapted Mobile App Rating Scale. Forty-seven participants enrolled (61% female, 92% primary language English, mean age 58.3 years). All owned smart devices, with 49% using mobile apps. Overall completion rate 68%, successfully recorded 41% cases. requested assistance completed challenges mainly related design instruction understandability. Interview responses reflected favorable perception voice-screening apps their features. Findings suggest that is promising tool acquisition setting. However, development improved User Interface/User Experience broader, diverse studies are needed usable tool.Level evidence: 3.

Language: Английский

Citations

0

Pain Management in Cancer Patients With Artificial Intelligence: Narrative Review DOI Creative Commons
Golnar Ghane, Raoofeh Karimi,

Amir Mohammad Chekeni

et al.

Scientifica, Journal Year: 2025, Volume and Issue: 2025(1)

Published: Jan. 1, 2025

Background: Pain is a significant symptom in cancer patients that frequently not effectively treated, and managing it seen as crucial aspect of caring for these patients. This severe pain causes disturbance their quality life. At present, there are different challenges utilizing range pharmacological nonpharmacological treatments Recent technological advancements, particularly artificial intelligence, have improved the management Artificial intelligence its algorithms offer potential solutions relief with reduced side effects. Study Design: The current review aimed to assess validity studies on using Four databases been used all published from start 2023: PubMed, Scopus, Web Science, Google Scholar. search mechanism articles was mainly valid mesh-based keywords, asking experts, reviewing literature including "Pain," "Pain management," "Cancer," "Artificial intelligence." During initial search, total 450 were found, after considering inclusion exclusion criteria abstract content articles, 15 finally included study. Results: AI-based can provide individual plans. When AI analyzes large patient data such physiological signals, responses treatment, symptoms who diagnosed pain, possible accurately adjust therapeutic measures. Conclusions: enables healthcare providers timely care assistance through remote monitoring telehealth services, even when they physically present. Despite presence hurdles ensuring ethical practices protecting privacy, integration oncology brings optimism future.

Language: Английский

Citations

0

Method Matters: Enhancing Voice‐Based Depression Detection With a New Data Collection Framework DOI Creative Commons
Dan Vilenchik, Julie Cwikel,

Yaakob Ezra

et al.

Depression and Anxiety, Journal Year: 2025, Volume and Issue: 2025(1)

Published: Jan. 1, 2025

Depression accounts for a major share of global disability‐adjusted life‐years (DALYs). Diagnosis typically requires psychiatrist or lengthy self‐assessments, which can be challenging symptomatic individuals. Developing reliable, noninvasive, and accessible detection methods is healthcare priority. Voice analysis offers promising approach early depression detection, potentially improving treatment access reducing costs. This paper presents novel pipeline that addresses several critical challenges in the field, including data imbalance, label quality, model generalizability. Our study utilizes high‐quality, high‐depression‐prevalence dataset collected from specialized chronic pain clinic, enabling robust even with limited sample size. We obtained lift accuracy up to 15% over 50–50 baseline our 52‐patient using 3‐fold cross‐validation test (which means train set n = 34, std 2.8%, p ‐value 0.01). further show combining voice‐only acoustic features single self‐report question (subject unit distress [SUDs]) significantly improves predictive accuracy. While relying on SUDs not always good practice, collection setting lacked incentives misrepresent status; were highly giving 86% accuracy; adding raises it 92%, exceeding stand‐alone potential 0.1. Further will enhance accuracy, supporting rapid, noninvasive method overcomes clinical barriers. These findings offer tool across settings.

Language: Английский

Citations

0

Digital Twins for Supporting Ageing Well: Approaches in Current Research and Innovation in Europe and Japan DOI Open Access
Jasmin Lehmann, Lorenz Granrath, Ryan Browne

et al.

Sustainability, Journal Year: 2024, Volume and Issue: 16(7), P. 3064 - 3064

Published: April 7, 2024

One of the central social challenges 21st century is society’s aging. AI provides numerous possibilities for meeting this challenge. In context, concept digital twins, based on Cyber-Physical Systems, offers an exciting prospect. The e-VITA project, in which a virtual coaching system elderly people being created, allows same to be assessed as model development. This white paper collects and presents relevant findings from research areas around twin technologies. Furthermore, we address ethical issues. shows that twins can usefully applied older adults. However, it also required technologies must further developed issues discussed appropriate framework. Finally, explains how project could pave way towards developing Digital Twin Ageing.

Language: Английский

Citations

2

Multimodal AI techniques for pain detection: integrating facial gesture and paralanguage analysis DOI Creative Commons
Rommel Gutierrez, Joselin García-Ortiz, William Villegas-Ch

et al.

Frontiers in Computer Science, Journal Year: 2024, Volume and Issue: 6

Published: July 29, 2024

Accurate pain detection is a critical challenge in healthcare, where communication and interpretation of often limit traditional subjective assessments. The current situation characterized by the need for more objective reliable methods to assess pain, especially patients who cannot effectively communicate their experiences, such as young children or critically ill individuals. Despite technological advances, effective integration artificial intelligence tools multifaceted accurate continues present significant challenges. Our proposal addresses this problem through an interdisciplinary approach, developing hybrid model that combines analysis facial gestures paralanguage using techniques. This contributes significantly field, allowing objective, accurate, sensitive individual variations. results obtained have been notable, with our achieving precision 92%, recall 90%, specificity 95%, demonstrating evident efficiency over conventional methodologies. clinical implications include possibility improving assessment various medical settings, faster interventions, thereby patients’ quality life.

Language: Английский

Citations

2

Design of Voice-Based Artificial Intelligence System for Patient Admission DOI
Kexin Chen,

Shoukun Deng,

Xinli Zhang

et al.

Published: Jan. 1, 2024

Language: Английский

Citations

0

Detecting Deepfake Voices Using a Novel Method for Authenticity Verification in Voice-Based Communication DOI
Aditya Kansara, Priya Kumari, Boppuru Rudra Prathap

et al.

Lecture notes in networks and systems, Journal Year: 2024, Volume and Issue: unknown, P. 397 - 405

Published: Jan. 1, 2024

Language: Английский

Citations

0