ReviewJournal of personalized medicine2024
Artificial Intelligence-Driven Diagnostic Processes and Comprehensive Multimodal Models in Pain Medicine.
Review in Journal of personalized medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
23 citing papers in PubMed.
- Beyond the Algorithm: A Critical and Evidence-Based Review of Artificial Intelligence in Chronic Pain Rehabilitation.Cureus · 2026Review
- Artificial Intelligence in Spine Neuroimaging: Diagnostic and Prognostic Utility of Novel Biomarkers in Lower Back Pain.Journal of clinical medicine · 2026Review
- Real-Time Pain Assessment from Electrodermal Activity Using Deep Learning.Sensors (Basel, Switzerland) · 2026Article
- The medial prefrontal cortex as an integrative hub in chronic pain: network mechanisms and the enabling role of artificial intelligence.BioPsychoSocial medicine · 2026Article
- Quality of ChatGPT-Generated Responses to Common Patient Questions About Peripheral Nerve Stimulation: A Cross-Sectional Study.Clinics and practice · 2026Article
- Article
- Artificial Intelligence, Informatics, and Pain in Aging.Clinics in geriatric medicine · 2026Review
- Pain assessment and determination methods with wearable sensors: a scoping review.Medical & biological engineering & computing · 2026Article
- Article
- AI applications across the cancer pain care Continuum: applications and future directions.Frontiers in pain research (Lausanne, Switzerland) · 2026Review
- Spinal Cord Stimulation in Painful Diabetic Neuropathy: Advances, Outcomes, and Future Directions.Biomedicines · 2025Review
- A roadmap for artificial intelligence in pain medicine: current status, opportunities, and requirements.Current opinion in anaesthesiology · 2025Review
- Bioengineering Support in the Assessment and Rehabilitation of Low Back Pain.Bioengineering (Basel, Switzerland) · 2025Review
- Pain Assessment in Osteoarthritis: Present Practices and Future Prospects Including the Use of Biomarkers and Wearable Technologies, and AI-Driven Personalized Medicine.Journal of orthopaedic research : official publication of the Orthopaedic Research Society · 2025Review
- Expert consensus on feasibility and application of automatic pain assessment in routine clinical use.Journal of anesthesia, analgesia and critical care · 2025Review
- The Role of Biomarkers in Acute Pain: A Narrative Review.Pain and therapy · 2025Review
- Machine Learning Clinical Decision Support for Interdisciplinary Multimodal Chronic Musculoskeletal Pain Treatment: Prospective Pilot Study of Patient Assessment and Prognostic Profile Validation.JMIR rehabilitation and assistive technologies · 2025Article
- Neuropathic Pain: A Comprehensive Bibliometric Analysis of Research Trends, Contributions, and Future Directions.Current pain and headache reports · 2025Review
- Consciousness Research Through Pain.Healthcare (Basel, Switzerland) · 2025Review
- Mixed pain: clinical practice recommendations.Frontiers in medicine · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Pain diagnosis remains a challenging task due to its subjective nature, the variability in pain expression among individuals, and the difficult assessment of the underlying biopsychosocial factors. In this complex scenario, artificial intelligence (AI) can offer the potential to enhance diagnostic accuracy, predict treatment outcomes, and personalize pain management strategies. This review aims to dissect the current literature on computer-aided diagnosis methods. It also discusses how AI-driven diagnostic strategies can be integrated into multimodal models that combine various data sources, such as facial expression analysis, neuroimaging, and physiological signals, with advanced AI techniques. Despite the significant advancements in AI technology, its widespread adoption in clinical settings faces crucial challenges. The main issues are ethical considerations related to patient privacy, biases, and the lack of reliability and generalizability. Furthermore, there is a need for high-quality real-world validation and the development of standardized protocols and policies to guide the implementation of these technologies in diverse clinical settings.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.