{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,21]],"date-time":"2025-11-21T07:06:03Z","timestamp":1763708763280,"version":"3.45.0"},"reference-count":60,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2025,11,21]],"date-time":"2025-11-21T00:00:00Z","timestamp":1763683200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2025,11,21]],"date-time":"2025-11-21T00:00:00Z","timestamp":1763683200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/501100006196","name":"University of Oulu","doi-asserted-by":"crossref","id":[{"id":"10.13039\/501100006196","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Med Syst"],"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Early diagnosis of osteoarthritis (OA) remains a critical unmet need due to the lack of reliable detection methods. Detecting OA at an early stage provides a valuable clinical window for implementing effective intervention strategies. Raman spectroscopy (RS) holds promise for improving predictive accuracy in detecting osteoarthritic changes at the molecular level, monitoring disease progression, and assessing severity. This study aimed to systematically evaluate the predictive performance of RS in OA assessment in human samples, thereby highlighting current advancements in the field. The search included PubMed\/Medline, Scopus, Web of Science, and IEEE for studies published up to July 31, 2024. Two authors individually screened the studies using Covidence software, and data extraction was based on predefined criteria. The Prediction Model Risk of Bias Assessment Tool was employed to evaluate the bias and applicability of the included studies. Ten studies met the inclusion criteria. Near-infrared excited RS was the most used RS technique. All included studies reported predictive accuracy ranging from 73% to 100% in preclinical settings for OA assessment. Although all studies performed internal validation, most had a high risk of bias and none reported external validation, which limits the generalizability of their findings. These findings underscore both the potential and current limitations of RS in OA assessment. Future research should prioritize larger sample sizes, external validation, and standardized RS protocols to improve reproducibility across diverse clinical settings.<\/jats:p>","DOI":"10.1007\/s10916-025-02304-x","type":"journal-article","created":{"date-parts":[[2025,11,21]],"date-time":"2025-11-21T05:31:40Z","timestamp":1763703100000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Predictive Performance of Raman Spectroscopy in Osteoarthritis: A Systematic Review"],"prefix":"10.1007","volume":"49","author":[{"ORCID":"https:\/\/orcid.org\/0009-0006-4756-5975","authenticated-orcid":false,"given":"Monira","family":"Yesmean","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3176-3081","authenticated-orcid":false,"given":"Bijay Ratna","family":"Shakya","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0009-0004-3409-9843","authenticated-orcid":false,"given":"Minna","family":"Mannerkorpi","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2850-5484","authenticated-orcid":false,"given":"Simo","family":"Saarakkala","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5815-0325","authenticated-orcid":false,"given":"Miia","family":"Jansson","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,11,21]]},"reference":[{"key":"2304_CR1","doi-asserted-by":"publisher","first-page":"2586","DOI":"10.3390\/diagnostics13152586","volume":"13","author":"J Ehmig","year":"2023","unstructured":"Ehmig J, Engel G, Lotz J, Lehmann W, Taheri S, Schilling AF, Seif Amir Hosseini A, Panahi B (2023) MR-Imaging in Osteoarthritis: Current Standard of Practice and Future Outlook. Diagnostics 13:2586","journal-title":"Diagnostics"},{"key":"2304_CR2","doi-asserted-by":"publisher","first-page":"e508","DOI":"10.1016\/S2665-9913(23)00163-7","volume":"5","author":"JD Steinmetz","year":"2023","unstructured":"Steinmetz JD, Culbreth GT, Haile LM, et al (2023) Global, regional, and national burden of osteoarthritis, 1990\u20132020 and projections to 2050: a systematic analysis for the Global Burden of Disease Study 2021. The Lancet Rheumatology 5:e508\u2013e522","journal-title":"The Lancet Rheumatology"},{"key":"2304_CR3","doi-asserted-by":"publisher","first-page":"4120","DOI":"10.3390\/ijms24044120","volume":"24","author":"S Semenistaja","year":"2023","unstructured":"Semenistaja S, Skuja S, Kadisa A, Groma V (2023) Healthy and Osteoarthritis-Affected Joints Facing the Cellular Crosstalk. IJMS 24:4120","journal-title":"IJMS"},{"key":"2304_CR4","doi-asserted-by":"publisher","first-page":"184","DOI":"10.1016\/j.joca.2021.04.020","volume":"30","author":"KD Allen","year":"2022","unstructured":"Allen KD, Thoma LM, Golightly YM (2022) Epidemiology of osteoarthritis. Osteoarthritis and Cartilage 30:184\u2013195","journal-title":"Osteoarthritis and Cartilage"},{"key":"2304_CR5","doi-asserted-by":"publisher","first-page":"1036","DOI":"10.3390\/jpm13071036","volume":"13","author":"R Shaikh","year":"2023","unstructured":"Shaikh R, Tafintseva V, Nippolainen E, Virtanen V, Solheim J, Zimmermann B, Saarakkala S, T\u00f6yr\u00e4s J, Kohler A, Afara IO (2023) Characterisation of Cartilage Damage via Fusing Mid-Infrared, Near-Infrared, and Raman Spectroscopic Data. JPM 13:1036","journal-title":"JPM"},{"key":"2304_CR6","doi-asserted-by":"publisher","first-page":"194","DOI":"10.3390\/biology9080194","volume":"9","author":"Y He","year":"2020","unstructured":"He Y, Li Z, Alexander PG, Ocasio-Nieves BD, Yocum L, Lin H, Tuan RS (2020) Pathogenesis of Osteoarthritis: Risk Factors, Regulatory Pathways in Chondrocytes, and Experimental Models. Biology 9:194","journal-title":"Biology"},{"key":"2304_CR7","doi-asserted-by":"publisher","first-page":"56","DOI":"10.1038\/s41392-023-01330-w","volume":"8","author":"Q Yao","year":"2023","unstructured":"Yao Q, Wu X, Tao C, Gong W, Chen M, Qu M, Zhong Y, He T, Chen S, Xiao G (2023) Osteoarthritis: pathogenic signaling pathways and therapeutic targets. Sig Transduct Target Ther 8:56","journal-title":"Sig Transduct Target Ther"},{"key":"2304_CR8","doi-asserted-by":"publisher","first-page":"5","DOI":"10.1148\/radiol.2020192498","volume":"296","author":"FW Roemer","year":"2020","unstructured":"Roemer FW, Demehri S, Omoumi P, Link TM, Kijowski R, Saarakkala S, Crema MD, Guermazi A (2020) State of the Art: Imaging of Osteoarthritis\u2014Revisited 2020. Radiology 296:5\u201321","journal-title":"Radiology"},{"key":"2304_CR9","doi-asserted-by":"publisher","first-page":"54","DOI":"10.3390\/diagnostics13010054","volume":"13","author":"CA Mallio","year":"2022","unstructured":"Mallio CA, Bernetti C, Agostini F, Mangone M, Paoloni M, Santilli G, Martina FM, Quattrocchi CC, Zobel BB, Bernetti A (2022) Advanced MR Imaging for Knee Osteoarthritis: A Review on Local and Brain Effects. Diagnostics 13:54","journal-title":"Diagnostics"},{"key":"2304_CR10","doi-asserted-by":"publisher","first-page":"913","DOI":"10.1016\/j.joca.2021.04.018","volume":"30","author":"FW Roemer","year":"2022","unstructured":"Roemer FW, Guermazi A, Demehri S, Wirth W, Kijowski R (2022) Imaging in Osteoarthritis. Osteoarthritis and Cartilage 30:913\u2013934","journal-title":"Osteoarthritis and Cartilage"},{"key":"2304_CR11","doi-asserted-by":"publisher","first-page":"e12008","DOI":"10.1002\/jeo2.12008","volume":"11","author":"DA Perico","year":"2024","unstructured":"Perico DA, Uribe AC, Ni\u00f1o SJ, et al (2024) A proposed modification to the Kellgren and Lawrence classification for knee osteoarthritis using a compartment-specific approach. J exp orthop 11:e12008","journal-title":"J exp orthop"},{"key":"2304_CR12","doi-asserted-by":"publisher","first-page":"7582","DOI":"10.21037\/qims-22-1392","volume":"13","author":"CL Piccolo","year":"2023","unstructured":"Piccolo CL, Mallio CA, Vaccarino F, Grasso RF, Zobel BB (2023) Imaging of knee osteoarthritis: a review of multimodal diagnostic approach. Quant Imaging Med Surg 13:7582\u20137595","journal-title":"Quant Imaging Med Surg"},{"key":"2304_CR13","doi-asserted-by":"publisher","first-page":"2267","DOI":"10.3390\/app13042267","volume":"13","author":"P Kasprzak","year":"2023","unstructured":"Kasprzak P, Szybowicz M, G\u0142owacki M (2023) Analysis of Bone Microstructural Changes Using Raman Spectroscopy in Women with Varus Deformity of the Knee Joint in the Course of the Primary Osteoarthritis. Applied Sciences 13:2267","journal-title":"Applied Sciences"},{"key":"2304_CR14","doi-asserted-by":"publisher","first-page":"404","DOI":"10.3390\/pr11020404","volume":"11","author":"AA Aziz","year":"2023","unstructured":"Aziz AA, Selvaratnam V, Fikri YFBA, Sani MSA, Kamarul T (2023) Diagnosis of Osteoarthritis at an Early Stage via Infrared Spectroscopy Combined Chemometrics in Human Serum: A Pilot Study. Processes 11:404","journal-title":"Processes"},{"key":"2304_CR15","doi-asserted-by":"publisher","first-page":"568","DOI":"10.1001\/jama.2020.22171","volume":"325","author":"JN Katz","year":"2021","unstructured":"Katz JN, Arant KR, Loeser RF (2021) Diagnosis and Treatment of Hip and Knee Osteoarthritis: A Review. JAMA 325:568","journal-title":"JAMA"},{"key":"2304_CR16","doi-asserted-by":"publisher","first-page":"2362","DOI":"10.3390\/diagnostics12102362","volume":"12","author":"JH Cueva","year":"2022","unstructured":"Cueva JH, Castillo D, Espin\u00f3s-Morat\u00f3 H, Dur\u00e1n D, D\u00edaz P, Lakshminarayanan V (2022) Detection and Classification of Knee Osteoarthritis. Diagnostics 12:2362","journal-title":"Diagnostics"},{"key":"2304_CR17","doi-asserted-by":"publisher","DOI":"10.5772\/intechopen.107310","author":"N Jean","year":"2023","unstructured":"Jean N, Salehi H, Maumus M, No\u00ebl D, Koffi-Gnagne Y, Cuisinier F (2023) Characterization of Degraded Cartilage Using Confocal Raman Microscopy. Cartilage Disorders - Recent Findings and Treatment. https:\/\/doi.org\/10.5772\/intechopen.107310","journal-title":"Cartilage Disorders - Recent Findings and Treatment"},{"key":"2304_CR18","doi-asserted-by":"publisher","first-page":"7","DOI":"10.1038\/s41413-023-00304-6","volume":"12","author":"X Fan","year":"2024","unstructured":"Fan X, Sun AR, Young RSE, Afara IO, Hamilton BR, Ong LJY, Crawford R, Prasadam I (2024) Spatial analysis of the osteoarthritis microenvironment: techniques, insights, and applications. Bone Res 12:7","journal-title":"Bone Res"},{"key":"2304_CR19","doi-asserted-by":"publisher","first-page":"392","DOI":"10.1002\/fft2.335","volume":"5","author":"Y Qi","year":"2024","unstructured":"Qi Y, Chen EX, Hu D, et al (2024) Applications of Raman spectroscopy in clinical medicine. Food Frontiers 5:392\u2013419","journal-title":"Food Frontiers"},{"key":"2304_CR20","doi-asserted-by":"publisher","first-page":"2300668","DOI":"10.1002\/advs.202300668","volume":"11","author":"Y Wang","year":"2024","unstructured":"Wang Y, Fang L, Wang Y, Xiong Z (2024) Current Trends of Raman Spectroscopy in Clinic Settings: Opportunities and Challenges. Advanced Science 11:2300668","journal-title":"Advanced Science"},{"key":"2304_CR21","doi-asserted-by":"publisher","first-page":"465","DOI":"10.1007\/s12553-019-00367-8","volume":"10","author":"F Le\u00f3n-Bejarano","year":"2020","unstructured":"Le\u00f3n-Bejarano F, Ram\u00edrez-El\u00edas M, M\u00e9ndez M, Guirado-L\u00f3pez R, Alba A, Rodr\u00edguez-Leyva I (2020) Analysis of vibrational modes from alpha-synuclein: a theoretical model using density functional theory and Raman spectroscopy. Health and Technology 10:465\u2013470","journal-title":"Health and Technology"},{"key":"2304_CR22","first-page":"5235","volume":"22","author":"C Yu","year":"2021","unstructured":"Yu C, Zhao B, Li Y, Zang H, Li L (2021) Vibrational Spectroscopy in Assessment of Early Osteoarthritis\u2014A Narrative Review. IJMS 22:5235","journal-title":"Narrative Review. IJMS"},{"key":"2304_CR23","doi-asserted-by":"publisher","first-page":"59","DOI":"10.25259\/JMSR_204_2023","volume":"8","author":"AK Al Ghaithi","year":"2024","unstructured":"Al Ghaithi AK, Almaskari SM, Almutani MM, Al Bimani AM, AL-Jabri Z, Al Badi KS, Husband J (2024) Advancing joint disease diagnosis: Molecular profiling and biomarker identification in synovial fluid using Raman spectroscopy. JMSR 8:59\u201365","journal-title":"JMSR"},{"key":"2304_CR24","doi-asserted-by":"publisher","first-page":"1203","DOI":"10.1366\/14-07592","volume":"68","author":"K Esmonde-White","year":"2014","unstructured":"Esmonde-White K (2014) Raman Spectroscopy of Soft Musculoskeletal Tissues. Appl Spectrosc 68:1203\u20131218","journal-title":"Appl Spectrosc"},{"key":"2304_CR25","doi-asserted-by":"publisher","first-page":"1237","DOI":"10.1002\/art.38360","volume":"66","author":"JG Kerns","year":"2014","unstructured":"Kerns JG, Gikas PD, Buckley K, et al (2014) Evidence from Raman Spectroscopy of a Putative Link Between Inherent Bone Matrix Chemistry and Degenerative Joint Disease. Arthritis & Rheumatology 66:1237\u20131246","journal-title":"Arthritis & Rheumatology"},{"key":"2304_CR26","doi-asserted-by":"publisher","first-page":"546","DOI":"10.3390\/diagnostics11030546","volume":"11","author":"P Casal-Beiroa","year":"2021","unstructured":"Casal-Beiroa P, Balboa-Barreiro V, Oreiro N, P\u00e9rtega-D\u00edaz S, Blanco FJ, Magalh\u00e3es J (2021) Optical Biomarkers for the Diagnosis of Osteoarthritis through Raman Spectroscopy: Radiological and Biochemical Validation Using Ex Vivo Human Cartilage Samples. Diagnostics 11:546","journal-title":"Diagnostics"},{"key":"2304_CR27","doi-asserted-by":"crossref","unstructured":"Faure E, Wegrzyn J, Bernabei I, Falgayrac G, Bertheaume N, Pascart T, Hugle T, Busso N, Nasi S (2024) A new ex vivo human model of osteoarthritis cartilage calcification. Rheumatology keae064:","DOI":"10.1016\/j.joca.2024.02.411"},{"key":"2304_CR28","doi-asserted-by":"publisher","first-page":"249","DOI":"10.1080\/05704928.2016.1226182","volume":"52","author":"L Rieppo","year":"2017","unstructured":"Rieppo L, T\u00f6yr\u00e4s J, Saarakkala S (2017) Vibrational spectroscopy of articular cartilage. Applied Spectroscopy Reviews 52:249\u2013266","journal-title":"Applied Spectroscopy Reviews"},{"key":"2304_CR29","doi-asserted-by":"publisher","first-page":"83","DOI":"10.21037\/aoj.2018.09.10","volume":"3","author":"E Pavlou","year":"2018","unstructured":"Pavlou E, Zhang X, Wang J, Kourkoumelis N (2018) Raman spectroscopy for the assessment of osteoarthritis. Ann Joint 3:83\u201383","journal-title":"Ann Joint"},{"key":"2304_CR30","doi-asserted-by":"publisher","first-page":"1171","DOI":"10.15562\/ism.v14i3.1855","volume":"14","author":"N Pradnyandari","year":"2023","unstructured":"Pradnyandari N (2023) Vibrational spectroscopy as a promising modality for diagnosing early osteoarthritis: a literature review. Intisari Sains Medis 14:1171\u20131175","journal-title":"Intisari Sains Medis"},{"key":"2304_CR31","doi-asserted-by":"crossref","unstructured":"Debray TPA, Damen JAAG, Snell KIE, Ensor J, Hooft L, Reitsma JB, Riley RD, Moons KGM (2017) A guide to systematic review and meta-analysis of prediction model performance. BMJ i6460","DOI":"10.1136\/bmj.i6460"},{"key":"2304_CR32","doi-asserted-by":"publisher","first-page":"388","DOI":"10.1001\/jama.2017.19163","volume":"319","author":"MDF McInnes","year":"2018","unstructured":"McInnes MDF, Moher D, Thombs BD, et al (2018) Preferred Reporting Items for a Systematic Review and Meta-analysis of Diagnostic Test Accuracy Studies: The PRISMA-DTA Statement. JAMA 319:388","journal-title":"JAMA"},{"key":"2304_CR33","doi-asserted-by":"publisher","first-page":"e1001744","DOI":"10.1371\/journal.pmed.1001744","volume":"11","author":"KGM Moons","year":"2014","unstructured":"Moons KGM, de Groot JAH, Bouwmeester W, Vergouwe Y, Mallett S, Altman DG, Reitsma JB, Collins GS (2014) Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modelling Studies: The CHARMS Checklist. PLoS Med 11:e1001744","journal-title":"PLoS Med"},{"key":"2304_CR34","doi-asserted-by":"publisher","first-page":"W1","DOI":"10.7326\/M18-1377","volume":"170","author":"KGM Moons","year":"2019","unstructured":"Moons KGM, Wolff RF, Riley RD, Whiting PF, Westwood M, Collins GS, Reitsma JB, Kleijnen J, Mallett S (2019) PROBAST: A Tool to Assess Risk of Bias and Applicability of Prediction Model Studies: Explanation and Elaboration. Ann Intern Med 170:W1","journal-title":"Ann Intern Med"},{"key":"2304_CR35","doi-asserted-by":"publisher","first-page":"e0274276","DOI":"10.1371\/journal.pone.0274276","volume":"18","author":"H Abdulazeem","year":"2023","unstructured":"Abdulazeem H, Whitelaw S, Schauberger G, Klug SJ (2023) A systematic review of clinical health conditions predicted by machine learning diagnostic and prognostic models trained or validated using real-world primary health care data. PLoS ONE 18:e0274276","journal-title":"PLoS ONE"},{"key":"2304_CR36","doi-asserted-by":"crossref","unstructured":"Boutron I, Page MJ, Higgins JP, Altman DG, Lundh A, Hr\u00f3bjartsson A, Cochrane Bias Methods G Considering bias and conflicts of interest among the included studies. In: Cochrane handbook for systematic reviews of interventions. Wiley, pp 177\u2013204","DOI":"10.1002\/9781119536604.ch7"},{"key":"2304_CR37","doi-asserted-by":"publisher","first-page":"8067","DOI":"10.1007\/s00216-015-8979-5","volume":"407","author":"R Kumar","year":"2015","unstructured":"Kumar R, Gr\u00f8nhaug KM, Afseth NK, Isaksen V, de Lange Davies C, Drogset JO, Lilledahl MB (2015) Optical investigation of osteoarthritic human cartilage (ICRS grade) by confocal Raman spectroscopy: a pilot study. Anal Bioanal Chem 407:8067\u20138077","journal-title":"Anal Bioanal Chem"},{"key":"2304_CR38","doi-asserted-by":"publisher","first-page":"9341","DOI":"10.3390\/ijms16059341","volume":"16","author":"R Kumar","year":"2015","unstructured":"Kumar R, Singh G, Gr\u00f8nhaug K, Afseth N, De Lange Davies C, Drogset J, Lilledahl M (2015) Single Cell Confocal Raman Spectroscopy of Human Osteoarthritic Chondrocytes: A Preliminary Study. IJMS 16:9341\u20139353","journal-title":"IJMS"},{"key":"2304_CR39","doi-asserted-by":"crossref","unstructured":"Crisford A, Cook H, Bourdakos K, Venkateswaran S, Dunlop D, Oreffo ROC, Mahajan S (2024) Harnessing Raman spectroscopy and multimodal imaging of cartilage for osteoarthritis diagnosis. Scientific Reports 14:","DOI":"10.1038\/s41598-024-83155-3"},{"key":"2304_CR40","doi-asserted-by":"publisher","first-page":"4264","DOI":"10.1364\/BOE.520171","volume":"15","author":"H Cook","year":"2024","unstructured":"Cook H, Crisford A, Bourdakos K, Dunlop D, Oreffo RO, Mahajan S (2024) Holistic vibrational spectromics assessment of human cartilage for osteoarthritis diagnosis. Biomed Opt Express 15:4264","journal-title":"Biomed Opt Express"},{"key":"2304_CR41","doi-asserted-by":"publisher","first-page":"1690","DOI":"10.1038\/s41598-023-28735-5","volume":"13","author":"M Cardinali","year":"2023","unstructured":"Cardinali M, Govoni M, Tschon M, et al (2023) Brillouin\u2013Raman micro-spectroscopy and machine learning techniques to classify osteoarthritic lesions in the human articular cartilage. Sci Rep 13:1690","journal-title":"Sci Rep"},{"key":"2304_CR42","doi-asserted-by":"publisher","first-page":"20299","DOI":"10.1038\/s41598-021-99569-2","volume":"11","author":"N Prokopi","year":"2021","unstructured":"Prokopi N, Andrikopoulos KS, Beobide AS, Voyiatzis GA, Papachristou DJ (2021) Collagen orientation probed by polarized Raman spectra can serve as differential diagnosis indicator between different grades of meniscus degeneration. Sci Rep 11:20299","journal-title":"Sci Rep"},{"key":"2304_CR43","doi-asserted-by":"publisher","first-page":"034013","DOI":"10.1117\/1.3130338","volume":"14","author":"KA Esmonde-White","year":"2009","unstructured":"Esmonde-White KA, Mandair GS, Raaii F, Jacobson JA, Miller BS, Urquhart AG, Roessler BJ, Morris MD (2009) Raman spectroscopy of synovial fluid as a tool for diagnosing osteoarthritis. J Biomed Opt 14:034013","journal-title":"J Biomed Opt"},{"key":"2304_CR44","doi-asserted-by":"crossref","unstructured":"Bocsa CD, Moisoiu V, Stefancu A, Leopold LF, Leopold N, Fodor D (2019) Knee osteoarthritis grading by resonant Raman and surface-enhanced Raman scattering (SERS) analysis of synovial fluid. Nanomedicine: Nanotechnology, Biology and Medicine 20:102012","DOI":"10.1016\/j.nano.2019.04.015"},{"key":"2304_CR45","doi-asserted-by":"publisher","first-page":"385","DOI":"10.1177\/00037028241285583","volume":"79","author":"V Tafintseva","year":"2025","unstructured":"Tafintseva V, Nippolainen E, Virtanen V, et al (2025) Machine Learning Approaches for the Fusion of Near-Infrared, Mid-Infrared, and Raman Data to Identify Cartilage Degradation in Human Osteochondral Plugs. Appl Spectrosc 79:385\u2013395","journal-title":"Appl Spectrosc"},{"key":"2304_CR46","doi-asserted-by":"publisher","first-page":"555","DOI":"10.1002\/jbio.201300200","volume":"8","author":"W Richardson","year":"2015","unstructured":"Richardson W, Wilkinson D, Wu L, Petrigliano F, Dunn B, Evseenko D (2015) Ensemble multivariate analysis to improve identification of articular cartilage disease in noisy Raman spectra. Journal of Biophotonics 8:555\u2013566","journal-title":"Journal of Biophotonics"},{"key":"2304_CR47","doi-asserted-by":"publisher","first-page":"949","DOI":"10.1089\/ten.teb.2021.0139","volume":"28","author":"M Fosca","year":"2022","unstructured":"Fosca M, Basoli V, Della Bella E, Russo F, Vadal\u00e0 G, Alini M, Rau JV, Verrier S (2022) Raman Spectroscopy in Skeletal Tissue Disorders and Tissue Engineering: Present and Prospective. Tissue Engineering Part B: Reviews 28:949\u2013965","journal-title":"Tissue Engineering Part B: Reviews"},{"key":"2304_CR48","doi-asserted-by":"publisher","first-page":"1537","DOI":"10.3390\/molecules26061537","volume":"26","author":"A Saletnik","year":"2021","unstructured":"Saletnik A, Saletnik B, Puchalski C (2021) Overview of Popular Techniques of Raman Spectroscopy and Their Potential in the Study of Plant Tissues. Molecules 26:1537","journal-title":"Molecules"},{"key":"2304_CR49","doi-asserted-by":"crossref","unstructured":"Bao Y, Wang H, Wu J, Dong J, Tang J, Shang H, Shang L, Qin J, Yin J (2021) Surface enhanced Raman scattering research on joint synovial fluid. In: 2021 IEEE International Conference on Manipulation, Manufacturing and Measurement on the Nanoscale (3\u00a0M-NANO). IEEE, Xi\u2019an, China, pp 5\u20138","DOI":"10.1109\/3M-NANO49087.2021.9599753"},{"key":"2304_CR50","doi-asserted-by":"publisher","first-page":"231","DOI":"10.1186\/s11671-019-3039-2","volume":"14","author":"RR Jones","year":"2019","unstructured":"Jones RR, Hooper DC, Zhang L, Wolverson D, Valev VK (2019) Raman Techniques: Fundamentals and Frontiers. Nanoscale Res Lett 14:231","journal-title":"Nanoscale Res Lett"},{"key":"2304_CR51","doi-asserted-by":"publisher","first-page":"100322","DOI":"10.1016\/j.apsadv.2022.100322","volume":"12","author":"S Kumar","year":"2022","unstructured":"Kumar S, Gahlaut SK, Singh JP (2022) Sculptured thin films: Overcoming the limitations of surface-enhanced Raman scattering substrates. Applied Surface Science Advances 12:100322","journal-title":"Applied Surface Science Advances"},{"key":"2304_CR52","doi-asserted-by":"publisher","first-page":"2203104","DOI":"10.1002\/adom.202203104","volume":"11","author":"Y Qi","year":"2023","unstructured":"Qi Y, Hu D, Jiang Y, Wu Z, Zheng M, Chen EX, Liang Y, Sadi MA, Zhang K, Chen YP (2023) Recent Progresses in Machine Learning Assisted Raman Spectroscopy. Advanced Optical Materials 11:2203104","journal-title":"Advanced Optical Materials"},{"key":"2304_CR53","doi-asserted-by":"publisher","first-page":"100012","DOI":"10.1016\/j.clispe.2021.100012","volume":"3","author":"R Gaifulina","year":"2021","unstructured":"Gaifulina R, Nunn ADG, Draper ERC, Strachan RK, Blake N, Firth S, Thomas GMH, McMillan PF, Dudhia J (2021) Intra-operative Raman spectroscopy and ex vivo Raman mapping for assessment of cartilage degradation. Clinical Spectroscopy 3:100012","journal-title":"Clinical Spectroscopy"},{"key":"2304_CR54","doi-asserted-by":"publisher","first-page":"2250027","DOI":"10.1142\/S1793545822500274","volume":"15","author":"R An","year":"2022","unstructured":"An R, Gu H, Guo Z, Zhong H, Wei H, Wu G, He Y, Xie S, Yang H (2022) Diagnosis of knee osteoarthritis by OCT and surface-enhanced Raman spectroscopy. J Innov Opt Health Sci 15:2250027","journal-title":"J Innov Opt Health Sci"},{"key":"2304_CR55","doi-asserted-by":"publisher","DOI":"10.1117\/1.JBO.27.11.115002","author":"R Asaoka","year":"2022","unstructured":"Asaoka R, Kiyomatsu H, Miura H, Jono A, Kinoshita T, Takao M, Katagiri T, Oshima Y (2022) Prognostic potential and pathological validation of a diagnostic application using Raman spectroscopy in the characterization of degenerative changes in the cartilage of the humeral head. J Biomed Opt. https:\/\/doi.org\/10.1117\/1.JBO.27.11.115002","journal-title":"J Biomed Opt"},{"key":"2304_CR56","doi-asserted-by":"publisher","first-page":"7428","DOI":"10.1039\/D0CS01019G","volume":"49","author":"NM Ralbovsky","year":"2020","unstructured":"Ralbovsky NM, Lednev IK (2020) Towards development of a novel universal medical diagnostic method: Raman spectroscopy and machine learning. Chem Soc Rev 49:7428\u20137453","journal-title":"Chem Soc Rev"},{"key":"2304_CR57","doi-asserted-by":"publisher","first-page":"2143","DOI":"10.1038\/s41596-020-0322-8","volume":"15","author":"CLM Morais","year":"2020","unstructured":"Morais CLM, Lima KMG, Singh M, Martin FL (2020) Tutorial: multivariate classification for vibrational spectroscopy in biological samples. Nat Protoc 15:2143\u20132162","journal-title":"Nat Protoc"},{"key":"2304_CR58","doi-asserted-by":"publisher","first-page":"31","DOI":"10.1145\/3236386.3241340","volume":"16","author":"Z Lipton","year":"2018","unstructured":"Lipton Z (2018) Mythos The of Model Interpretability. Queue 16:31\u201357","journal-title":"Queue"},{"key":"2304_CR59","doi-asserted-by":"publisher","first-page":"1759720X2311581","DOI":"10.1177\/1759720X231158198","volume":"15","author":"A Xuan","year":"2023","unstructured":"Xuan A, Chen H, Chen T, et al (2023) The application of machine learning in early diagnosis of osteoarthritis: a narrative review. Therapeutic Advances in Musculoskeletal 15:1759720X231158198","journal-title":"Therapeutic Advances in Musculoskeletal"},{"key":"2304_CR60","doi-asserted-by":"publisher","first-page":"231","DOI":"10.1136\/bmjqs-2018-008370","volume":"28","author":"R Challen","year":"2019","unstructured":"Challen R, Denny J, Pitt M, Gompels L, Edwards T, Tsaneva-Atanasova K (2019) Artificial intelligence, bias and clinical safety. BMJ Qual Saf 28:231\u2013237","journal-title":"BMJ Qual Saf"}],"container-title":["Journal of Medical Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10916-025-02304-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10916-025-02304-x\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10916-025-02304-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,11,21]],"date-time":"2025-11-21T07:03:27Z","timestamp":1763708607000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10916-025-02304-x"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,11,21]]},"references-count":60,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2025,12]]}},"alternative-id":["2304"],"URL":"https:\/\/doi.org\/10.1007\/s10916-025-02304-x","relation":{},"ISSN":["1573-689X"],"issn-type":[{"type":"electronic","value":"1573-689X"}],"subject":[],"published":{"date-parts":[[2025,11,21]]},"assertion":[{"value":"16 June 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"11 November 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"21 November 2025","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"This study is a systematic review. Ethical approval was not required, as no individual-level data were collected or reported.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics Approval"}},{"value":"Not applicable.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Clinical Trial Number"}},{"value":"The authors declare no competing interests","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests."}}],"article-number":"166"}}