{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T01:20:54Z","timestamp":1760059254842,"version":"build-2065373602"},"reference-count":40,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2025,5,31]],"date-time":"2025-05-31T00:00:00Z","timestamp":1748649600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Italian Ministry of Foreign Affairs and International Cooperation","award":["PGR02067"],"award-info":[{"award-number":["PGR02067"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Oral caries is one of the most common oral diseases worldwide, affecting about 2.4 billion people. This phenomenon always starts with enamel demineralization, eventually progressing to tooth cavitation and loss when not properly treated. Nowadays, the standard diagnostic techniques to detect demineralization strongly depend on the operator\u2019s expertise and are characterized by fairly low sensitivity and specificity, and\/or involve ionizing radiation. This study investigates the feasibility of a non-invasive, effective, rapid, and radiation-free approach employing impedance spectroscopy for early caries detection. Two binary classifiers were developed for automated assessment and validated using a dataset obtained by in vitro demineralization of human teeth. A computationally efficient single-neuron classifier, utilizing a single impedance phase measurement at 15 Hz, achieved 88% accuracy, offering a lightweight, low-power solution suitable for microcontroller implementation and rapid measurements. A Multi-Layer Perceptron (MLP) classifier, utilizing equivalent circuit element values, yielded a similar accuracy of 86%. A prototype of a diagnostic portable tool was developed and characterized, demonstrating reliable impedance phase measurement (uncertainty &lt; 2\u00b0). The performance of these classifiers meets or exceeds the existing AI-based methodologies for caries detection relying on radiographic data. This work introduces a novel application of AI to tooth impedance spectra, addressing a significant research gap in non-invasive diagnostics and laying the foundation for a novel, accessible, and accurate tool for early caries management.<\/jats:p>","DOI":"10.3390\/s25113476","type":"journal-article","created":{"date-parts":[[2025,6,2]],"date-time":"2025-06-02T08:34:13Z","timestamp":1748853253000},"page":"3476","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Classification Algorithms for Early Tooth Demineralization Assessment by Impedance Spectroscopy"],"prefix":"10.3390","volume":"25","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8804-722X","authenticated-orcid":false,"given":"Isabella","family":"Sannino","sequence":"first","affiliation":[{"name":"Department of Applied Science and Technology, Politecnico di Torino, 10129 Turin, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Luca","family":"Lombardo","sequence":"additional","affiliation":[{"name":"Department of Electronics and Telecommunications, Politecnico di Torino, 10129 Turin, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6463-9311","authenticated-orcid":false,"given":"Leila","family":"Es Sebar","sequence":"additional","affiliation":[{"name":"Department of Applied Science and Technology, Politecnico di Torino, 10129 Turin, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9723-6188","authenticated-orcid":false,"given":"Marco","family":"Parvis","sequence":"additional","affiliation":[{"name":"Department of Electronics and Telecommunications, Politecnico di Torino, 10129 Turin, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4057-1428","authenticated-orcid":false,"given":"Allegra","family":"Comba","sequence":"additional","affiliation":[{"name":"Department of Surgical Science, Universit\u00e0 degli Studi di Torino, 10124 Turin, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7380-1675","authenticated-orcid":false,"given":"Nicola","family":"Scotti","sequence":"additional","affiliation":[{"name":"Department of Surgical Science, Universit\u00e0 degli Studi di Torino, 10124 Turin, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Emma","family":"Angelini","sequence":"additional","affiliation":[{"name":"Department of Applied Science and Technology, Politecnico di Torino, 10129 Turin, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1996-1958","authenticated-orcid":false,"given":"Leonardo","family":"Iannucci","sequence":"additional","affiliation":[{"name":"Department of Applied Science and Technology, Politecnico di Torino, 10129 Turin, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tolou","family":"Shokuhfar","sequence":"additional","affiliation":[{"name":"Department of Biomedical Engineering, University of Illinois, Chicago, IL 60607, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sabrina","family":"Grassini","sequence":"additional","affiliation":[{"name":"Department of Applied Science and Technology, Politecnico di Torino, 10129 Turin, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2025,5,31]]},"reference":[{"key":"ref_1","unstructured":"World Health Organization (2023). Global Oral Health Status Report: Towards Universal Health Coverage for Oral Health by 2030. Regional Summary of the African Region, World Health Organization."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Jain, N., Dutt, U., Radenkov, I., and Jain, S. (2023). WHO\u2019s Global oral Health Status Report 2022: Actions, Discussion and Implementation, World Health Organization.","DOI":"10.1111\/odi.14516"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"650","DOI":"10.1177\/0022034515573272","article-title":"Global burden of untreated caries: A systematic review and meta-regression","volume":"94","author":"Kassebaum","year":"2015","journal-title":"J. Dent. Res."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"35","DOI":"10.1177\/154405910408301s07","article-title":"What constitutes dental caries? Histopathology of carious enamel and dentin related to the action of cariogenic biofilms","volume":"83","author":"Kidd","year":"2004","journal-title":"J. Dent. Res."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"4743","DOI":"10.2147\/IJN.S107624","article-title":"Demineralization\u2013remineralization dynamics in teeth and bone","volume":"11","author":"Aljabo","year":"2016","journal-title":"Int. J. Nanomed."},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Melo, M., Sanz, J.L., Forner, L., Rodr\u00edguez-Lozano, F.J., and Guerrero-Giron\u00e9s, J. (2022). Current Status and Trends in Research on Caries Diagnosis: A Bibliometric Analysis. Int. J. Environ. Res. Public Health, 19.","DOI":"10.3390\/ijerph19095011"},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Carn\u0131, D., Grimaldi, D., Sciammarella, P.F., Nastro, A., Lamonaca, F., and Vasile, M. (2016, January 15\u201318). Measurement technique for the healty and carious teeth based on thermal analysis. Proceedings of the 2016 IEEE International Symposium on Medical Measurements and Applications (MeMeA), Benevento, Italy.","DOI":"10.1109\/MeMeA.2016.7533728"},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"AbdELkader, A.R., Hafez Ibrahim, S., and Elsayed Hassanein, O. (2024). Reliability of impedance spectroscopy versus digital radiograph and ICDAS-II in occlusal caries detection: A prospective clinical trial. Sci. Rep., 14.","DOI":"10.1038\/s41598-024-66627-4"},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"AbuSalim, S., Zakaria, N., Islam, M.R., Kumar, G., Mokhtar, N., and Abdulkadir, S.J. (2022). Analysis of deep learning techniques for dental informatics: A systematic literature review. Healthcare, 10.","DOI":"10.3390\/healthcare10101892"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"62","DOI":"10.1016\/j.acra.2019.10.001","article-title":"Artificial intelligence in medicine: Where are we now?","volume":"27","author":"Kulkarni","year":"2020","journal-title":"Acad. Radiol."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"20180218","DOI":"10.1259\/dmfr.20180218","article-title":"A deep-learning artificial intelligence system for assessment of root morphology of the mandibular first molar on panoramic radiography","volume":"48","author":"Hiraiwa","year":"2019","journal-title":"Dentomaxillofac. Radiol."},{"key":"ref_12","first-page":"e41694","article-title":"Transforming dental caries diagnosis through artificial intelligence-based techniques","volume":"15","author":"Anil","year":"2023","journal-title":"Cureus"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"104115","DOI":"10.1016\/j.jdent.2022.104115","article-title":"Deep learning for caries detection: A systematic review: DL for Caries Detection","volume":"122","author":"Motamedian","year":"2022","journal-title":"J. Dent."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"468","DOI":"10.1007\/s11282-021-00577-9","article-title":"Deep-learning approach for caries detection and segmentation on dental bitewing radiographs","volume":"38","author":"Bayrakdar","year":"2022","journal-title":"Oral Radiol."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Lin, X., Hong, D., Zhang, D., Huang, M., and Yu, H. (2022). Detecting proximal caries on periapical radiographs using convolutional neural networks with different training strategies on small datasets. Diagnostics, 12.","DOI":"10.3390\/diagnostics12051047"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"103425","DOI":"10.1016\/j.jdent.2020.103425","article-title":"Detecting caries lesions of different radiographic extension on bitewings using deep learning","volume":"100","author":"Cantu","year":"2020","journal-title":"J. Dent."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"5255","DOI":"10.1007\/s11042-020-09891-6","article-title":"GV Black dental caries classification and preparation technique using optimal CNN-LSTM classifier","volume":"80","author":"Singh","year":"2021","journal-title":"Multimed. Tools Appl."},{"key":"ref_18","first-page":"312","article-title":"Image segmentation techniques application for the diagnosis of dental caries","volume":"Volume 1","year":"2020","journal-title":"Advances in Emerging Trends and Technologies"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"28843","DOI":"10.1007\/s11042-018-6035-0","article-title":"Automatic computer-aided caries detection from dental X-ray images using intelligent level set","volume":"77","author":"Rad","year":"2018","journal-title":"Multimed. Tools Appl."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"103260","DOI":"10.1016\/j.jdent.2019.103260","article-title":"Deep learning for caries lesion detection in near-infrared light transillumination images: A pilot study","volume":"92","author":"Schwendicke","year":"2020","journal-title":"J. Dent."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"106","DOI":"10.1016\/j.jdent.2018.07.015","article-title":"Detection and diagnosis of dental caries using a deep learning-based convolutional neural network algorithm","volume":"77","author":"Lee","year":"2018","journal-title":"J. Dent."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"4660","DOI":"10.1166\/jctn.2020.9295","article-title":"Dental caries classification system using deep learning based convolutional neural network","volume":"17","year":"2020","journal-title":"J. Comput. Theor. Nanosci."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"76","DOI":"10.1177\/154405910408301s15","article-title":"Electrical measurements for use in caries clinical trials","volume":"83","author":"Longbottom","year":"2004","journal-title":"J. Dent. Res."},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Es Sebar, L., Angelini, E., Grassini, S., Iannucci, L., and Parvis, M. (2020, January 25\u201328). An op amp-less electrochemical impedance spectroscopy system. Proceedings of the 2020 IEEE International Instrumentation and Measurement Technology Conference (I2MTC), Dubrovnik, Croatia.","DOI":"10.1109\/I2MTC43012.2020.9129355"},{"key":"ref_25","first-page":"CD014547","article-title":"Electrical conductance for the detection of dental caries","volume":"3","author":"Group","year":"2021","journal-title":"Cochrane Database Syst. Rev."},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Litzenburger, F., Sch\u00e4fer, G., Hickel, R., K\u00fchnisch, J., and Heck, K. (2021). Comparison of novel and established caries diagnostic methods: A clinical study on occlusal surfaces. BMC Oral Health, 21.","DOI":"10.1186\/s12903-021-01465-8"},{"key":"ref_27","first-page":"293","article-title":"In-vivo performance of impedance spectroscopy, laser fluorescence, and bitewing radiographs for occlusal caries detection","volume":"49","author":"Mortensen","year":"2018","journal-title":"Quintessence Int."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"1090","DOI":"10.1177\/00220345211014799","article-title":"Dentin cross-linking effect of carbodiimide after 5 years","volume":"100","author":"Maravic","year":"2021","journal-title":"J. Dent. Res."},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Sannino, I., Es Sebar, L., Lombardo, L., Parvis, M., Comba, A., Scotti, N., Angelini, E., and Grassini, S. (2024, January 26\u201328). Integrating Impedance Spectroscopy and Perceptron-Based Classification for Tooth Treatment Monitoring. Proceedings of the 2024 IEEE International Symposium on Medical Measurements and Applications (MeMeA), Eindhoven, The Netherlands.","DOI":"10.1109\/MeMeA60663.2024.10596925"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"175","DOI":"10.1177\/08959374950090030101","article-title":"The application of in vitro models to research on demineralization and remineralization of the teeth","volume":"9","author":"White","year":"1995","journal-title":"Adv. Dent. Res."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"81","DOI":"10.1159\/000261348","article-title":"Progression and surface ultrastructure of in vitro caused erosive lesions in human and bovine enamel","volume":"25","author":"Meurman","year":"1991","journal-title":"Caries Res."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"264","DOI":"10.1016\/j.jdent.2008.11.020","article-title":"In vitro demineralization of human enamel natural and abraded surfaces: A micromechanical and SEM investigation","volume":"37","author":"Xue","year":"2009","journal-title":"J. Dent."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"21","DOI":"10.1590\/S0103-64402008000100004","article-title":"pH-Cycling models to evaluate the effect of low fluoride dentifrice on enamel de-and remineralization","volume":"19","author":"Queiroz","year":"2008","journal-title":"Braz. Dent. J."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"146","DOI":"10.1590\/0103-6440201302316","article-title":"Assessment of Tooth Structure using an Alternative Electrical Bioimpedance Spectroscopy Method","volume":"25","author":"Morais","year":"2014","journal-title":"Braz. Dent. J."},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Herencsar, N., Freeborn, T.J., Kartci, A., and Cicekoglu, O. (2020). A Comparative Study of Two Fractional-Order Equivalent Electrical Circuits for Modeling the Electrical Impedance of Dental Tissues. Entropy, 22.","DOI":"10.3390\/e22101117"},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Berezhanska, M., Godinho, D.M., Mal\u00f3, P., and Concei\u00e7\u00e3o, R.C. (2023). Dielectric characterization of healthy human teeth from 0.5 to 18 ghz with an open-ended coaxial probe. Sensors, 23.","DOI":"10.3390\/s23031617"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"20180250","DOI":"10.1259\/dmfr.20180250","article-title":"An ex vivo comparative study of occlusal and proximal caries using terahertz and X-ray imaging","volume":"48","author":"Altan","year":"2019","journal-title":"Dentomaxillofac. Radiol."},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Koyama, T., Kakino, S., and Matsuura, Y. (2018). A feasibility study of photoacoustic detection of hidden dental caries using a fiber-based imaging system. Appl. Sci., 8.","DOI":"10.3390\/app8040621"},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"Sannino, I., Iannucci, L., Lombardo, L., Parvis, M., Comba, A., Arpaia, P., Angelini, E., and Grassini, S. (2023, January 14\u201316). Impedance measurements for demineralized tooth lesions assessment. Proceedings of the 2023 IEEE International Symposium on Medical Measurements and Applications (MeMeA), Jeju, Republic of Korea.","DOI":"10.1109\/MeMeA57477.2023.10171893"},{"key":"ref_40","first-page":"2825","article-title":"Scikit-learn: Machine Learning in Python","volume":"12","author":"Pedregosa","year":"2011","journal-title":"J. Mach. Learn. Res."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/25\/11\/3476\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,9]],"date-time":"2025-10-09T17:44:45Z","timestamp":1760031885000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/25\/11\/3476"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,5,31]]},"references-count":40,"journal-issue":{"issue":"11","published-online":{"date-parts":[[2025,6]]}},"alternative-id":["s25113476"],"URL":"https:\/\/doi.org\/10.3390\/s25113476","relation":{},"ISSN":["1424-8220"],"issn-type":[{"type":"electronic","value":"1424-8220"}],"subject":[],"published":{"date-parts":[[2025,5,31]]}}}