The integration of digital technologies into oral health care is transforming the field, driving advancements in diagnostic precision, patient engagement, and access to care. This review evaluates the impact of mobile health (mHealth) applications, tele-dentistry, artificial intelligence (AI), wearable devices, and advanced imaging systems on modern dentistry. Synthesizing findings from 125 studies published between 2010 and 2024, the paper identifies key achievements, including improved patient compliance, enhanced diagnostic capabilities, and expanded access to care in underserved areas. Tele-dentistry has been pivotal in bridging geographical gaps, particularly during the COVID-19 pandemic, while AI tools have revolutionized diagnostics and personalized treatment planning. Wearable devices and mHealth applications have empowered patients with real-time feedback, fostering sustained adherence to oral hygiene practices. The review also highlights the potential of digital tools to reduce healthcare disparities and operational costs, paving the way for more equitable and efficient dental care. By outlining critical advancements and future directions, this paper underscores the transformative potential of digital health technologies in dentistry. It advocates for further research on data security, interoperability, and innovative applications of AI to maximize the benefits of these tools, ultimately shaping a more accessible and patient-focused oral health ecosystem.
References
[1]
Yeung, A.W.K., Torkamani, A., Butte, A.J., Glicksberg, B.S., Schuller, B., Rodriguez, B., et al. (2023) The Promise of Digital Healthcare Technologies. FrontiersinPublicHealth, 11, Article 1196596. https://doi.org/10.3389/fpubh.2023.1196596
[2]
Hung, M., Lipsky, M.S., Phuatrakoon, T.N., Nguyen, M., Licari, F.W. and Unni, E.J. (2022) Teledentistry Implementation during the COVID-19 Pandemic: Scoping Review. InteractiveJournalofMedicalResearch, 11, e39955. https://doi.org/10.2196/39955
[3]
Khanagar, S.B., Alfouzan, K., Awawdeh, M., Alkadi, L., Albalawi, F. and Alfadley, A. (2022) Application and Performance of Artificial Intelligence Technology in Detection, Diagnosis and Prediction of Dental Caries (DC)—A Systematic Review. Diagnostics, 12, Article 1083. https://doi.org/10.3390/diagnostics12051083
[4]
Warmling, C.M., Spin-Neto, R., Palma, L.Z., Silva-Junior, M.F., Castro, R.G., Finkler, M., et al. (2023) Impact of the COVID-19 Pandemic on the Oral Health Workforce: A Multicenter Study from the Southern Region of Brazil. InternationalJournalofEnvironmentalResearchandPublicHealth, 20, Article 1301. https://doi.org/10.3390/ijerph20021301
[5]
Zych, M.M., Bond, R., Mulvenna, M., Martinez Carracedo, J., Bai, L. and Leigh, S. (2024) Quality Assessment of Digital Health Apps: Umbrella Review. JournalofMedicalInternetResearch, 26, e58616. https://doi.org/10.2196/58616
[6]
Németh, O., Uhrin, E., Girasek, E., Boros, J. and Győrffy, Z. (2023) The Impact of Digital Healthcare and Teledentistry on Dentistry in the 21st Century: A Survey of Hungarian Dentists. BMCOralHealth, 23, Article No. 1025. https://doi.org/10.1186/s12903-023-03770-w
[7]
Joda, T., Bornstein, M.M., Jung, R.E., Ferrari, M., Waltimo, T. and Zitzmann, N.U. (2020) Recent Trends and Future Direction of Dental Research in the Digital Era. InternationalJournalofEnvironmentalResearchandPublicHealth, 17, Article 1987. https://doi.org/10.3390/ijerph17061987
[8]
Umer, M.F., Faheemuddin, M., Alshehri, Y.A., Algosaibi, A.A., Alojail, A.A., Althani, A.A., et al. (2024) Assessment of Digital Dentistry Knowledge and Practices among Dental Students at King Faisal University, Saudi Arabia. MedicalScienceMonitor, 30, e944692. https://doi.org/10.12659/msm.944692
[9]
Lee, J., Choi, M., Lee, S.A. and Jiang, N. (2018) Effective Behavioral Intervention Strategies Using Mobile Health Applications for Chronic Disease Management: A Systematic Review. BMCMedicalInformaticsandDecisionMaking, 18, Article No. 12. https://doi.org/10.1186/s12911-018-0591-0
[10]
Favaretto, M., Shaw, D., De Clercq, E., Joda, T. and Elger, B.S. (2020) Big Data and Digitalization in Dentistry: A Systematic Review of the Ethical Issues. InternationalJournalofEnvironmentalResearchandPublicHealth, 17, Article 2495. https://doi.org/10.3390/ijerph17072495
[11]
Bastani, P., Manchery, N., Samadbeik, M., Ha, D. and Do, L. (2022) Digital Health in Children’s Oral and Dental Health: An Overview and a Bibliometric Analysis. Children, 9, Article 1039. https://doi.org/10.3390/children9071039
[12]
Semerci, Z.M. and Yardımcı, S. (2024) Empowering Modern Dentistry: The Impact of Artificial Intelligence on Patient Care and Clinical Decision Making. Diagnostics, 14, Article 1260. https://doi.org/10.3390/diagnostics14121260
[13]
Surdu, A., Budala, D.G., Luchian, I., Foia, L.G., Botnariu, G.E. and Scutariu, M.M. (2024) Using AI in Optimizing Oral and Dental Diagnoses—A Narrative Review. Diagnostics, 14, Article 2804. https://doi.org/10.3390/diagnostics14242804
[14]
Brown, A.L. and Johnson, E. (2021) The Impact of Mobile Health Applications on Oral Hygiene Adherence: A Randomized Control Trial. Journal of Dental Research, 100, 1025-1032.
[15]
Sharaf, M. and Abou El Fadl, R.K. (2024) Prospective Acceptability of Using mHealth Interventions for Oral Health Promotion in a Sample of Egyptian Women: A Cross-Sectional Study. DigitalHealth, 10, 10. https://doi.org/10.1177/20552076241301272
[16]
Thorat, V., Rao, P., Joshi, N., Talreja, P. and Shetty, A.R. (2024) Role of Artificial Intelligence (AI) in Patient Education and Communication in Dentistry. Cureus, 16, e59799. https://doi.org/10.7759/cureus.59799
[17]
Valeri, C., Quinzi, V., Di Giandomenico, D., Fani, E., Leonardi, R. and Marzo, G. (2023) Teledentistry: A Bibliometric Analysis of the Scientific Publication’s Trend. Digital Health, 9, 12. https://doi.org/10.1177/20552076231204747
[18]
Estai, M., et al. (2020) Tele-Dentistry as a Means to Improve Access to Oral Health Care: A Systematic Review. BMC Oral Health, 14, 20.
[19]
Niknam, F., Sharifian, R., Bashiri, A., Mardani, M., Akbari, R., Tuffaha, H., et al. (2023) Tele-dentistry, Its Trends, Scope, and Future Framework in Oral Medicine; a Scoping Review during January 1999 to December 2021. ArchivesofPublicHealth, 81, Article No. 104. https://doi.org/10.1186/s13690-023-01128-w
[20]
Alam, M.K., Alftaikhah, S.A.A., Issrani, R., Ronsivalle, V., Lo Giudice, A., Cicciù, M., et al. (2024) Applications of Artificial Intelligence in the Utilisation of Imaging Modalities in Dentistry: A Systematic Review and Meta-Analysis of In-Vitro Studies. Heliyon, 10, e24221. https://doi.org/10.1016/j.heliyon.2024.e24221
[21]
El Tantawi, M., Lam, W.Y.H., Giraudeau, N., Virtanen, J.I., Matanhire, C., Chifamba, T., et al. (2023) Teledentistry from Research to Practice: A Tale of Nineteen Countries. FrontiersinOralHealth, 4, Article 1188557. https://doi.org/10.3389/froh.2023.1188557
[22]
Ahmed, N., Abbasi, M.S., Zuberi, F., Qamar, W., Halim, M.S.B., Maqsood, A., et al. (2021) Artificial Intelligence Techniques: Analysis, Application, and Outcome in Dentistry—A Systematic Review. BioMedResearchInternational, 2021, Article ID: 9751564. https://doi.org/10.1155/2021/9751564
[23]
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, Article 1892. https://doi.org/10.3390/healthcare10101892
[24]
Hung, M., Voss, M.W., Rosales, M.N., Li, W., Su, W., Xu, J., et al. (2019) Application of Machine Learning for Diagnostic Prediction of Root Caries. Gerodontology, 36, 395-404. https://doi.org/10.1111/ger.12432
[25]
Thurzo, A., Urbanová, W., Novák, B., Czako, L., Siebert, T., Stano, P., et al. (2022) Where Is the Artificial Intelligence Applied in Dentistry? Systematic Review and Literature Analysis. Healthcare, 10, Article 1269. https://doi.org/10.3390/healthcare10071269
[26]
Raja’a, M. and Farid, F. (2016) Computer-Based Technologies in Dentistry: Types and Applications. Journal of Dentistry, 13, 215-222.
[27]
Lo Barco, T., Kuchenbuch, M., Garcelon, N., Neuraz, A. and Nabbout, R. (2021) Improving Early Diagnosis of Rare Diseases Using Natural Language Processing in Unstructured Medical Records: An Illustration from Dravet Syndrome. OrphanetJournalofRareDiseases, 16, Article No. 309. https://doi.org/10.1186/s13023-021-01936-9
[28]
Yu, H., Zhang, J., Zhao, H. and Wang, W. (2020) Application of Support Vector Machines for Classification of Dental Lesions in Radiographic Images. Journal of Biomedical Informatics, 107, Article ID: 103484.
[29]
Alauddin, M.S., Baharuddin, A.S. and Mohd Ghazali, M.I. (2021) The Modern and Digital Transformation of Oral Health Care: A Mini Review. Healthcare, 9, Article 118. https://doi.org/10.3390/healthcare9020118
[30]
Kim, H. and Zhang, X. (2023) Reinforcement Learning in Personalized Orthodontic Care. International Journal of Advanced Orthodontic Technology, 5, 125-136.
[31]
Khan, I.M., Mani, S.A., Doss, J.G., Danaee, M. and Kong, L.Y.L. (2021) Pre-schoolers’ Tooth Brushing Behaviour and Association with Their Oral Health: A Cross Sectional Study. BMCOralHealth, 21, Article No. 283. https://doi.org/10.1186/s12903-021-01643-8
[32]
Graves, A., Grahl, T., Keiserman, M. and Kingsley, K. (2023) Systematic Review and Meta Analysis of the Relative Effect on Plaque Index among Pediatric Patients Using Powered (Electric) versus Manual Toothbrushes. DentistryJournal, 11, Article 46. https://doi.org/10.3390/dj11020046
[33]
Nzabonimana, E., Malele-Kolisa, Y. and Hlongwa, P. (2024) The Feasibility and Acceptability of a Mobile Application for Oral Health Education among Adults in Rwanda. Clinical, CosmeticandInvestigationalDentistry, 16, 359-369. https://doi.org/10.2147/ccide.s481599
[34]
Mahesh Batra, A. and Reche, A. (2023) A New Era of Dental Care: Harnessing Artificial Intelligence for Better Diagnosis and Treatment. Cureus, 15, e49319. https://doi.org/10.7759/cureus.49319
[35]
Marinho-Vieira, L.E., Martins, L.A.C., Freitas, D.Q., Haiter-Neto, F. and Oliveira, M.L. (2023) Revisiting Dynamic Range and Image Enhancement Ability of Contemporary Digital Radiographic Systems—Part 2: A Subjective Assessment. DentomaxillofacialRadiology, 52, Article ID: 20220370. https://doi.org/10.1259/dmfr.20220370
[36]
MacDonald, D. and Telyakova, V. (2024) An Overview of Cone-Beam Computed Tomography and Dental Panoramic Radiography in Dentistry in the Community. Tomography, 10, 1222-1237. https://doi.org/10.3390/tomography10080092
[37]
Lin, C., Goncalves, N., Scully, B., Heredia, R. and Hegde, S. (2022) A Teledentistry Pilot Study on Patient-Initiated Care. InternationalJournalofEnvironmentalResearchandPublicHealth, 19, Article 9403. https://doi.org/10.3390/ijerph19159403
[38]
Park, W.J. and Park, J. (2018) History and Application of Artificial Neural Networks in Dentistry. EuropeanJournalofDentistry, 12, 594-601. https://doi.org/10.4103/ejd.ejd_325_18
[39]
Rezaie, F., Farshbaf, M., Dahri, M., Masjedi, M., Maleki, R., Amini, F., et al. (2023) 3D Printing of Dental Prostheses: Current and Emerging Applications. JournalofCompositesScience, 7, Article 80. https://doi.org/10.3390/jcs7020080
[40]
Surendran, A., Daigavane, P., Shrivastav, S., Kamble, R., Sanchla, A.D., Bharti, L., et al. (2024) The Future of Orthodontics: Deep Learning Technologies. Cureus, 16, e62045. https://doi.org/10.7759/cureus.62045
[41]
Bonny, T., Al Nassan, W., Obaideen, K., Al Mallahi, M.N., Mohammad, Y. and El-damanhoury, H.M. (2023) Contemporary Role and Applications of Artificial Intelligence in Dentistry. F1000Research, 12, Article 1179. https://doi.org/10.12688/f1000research.140204.1
[42]
Mallineni, S.K., Sethi, M., Punugoti, D., Kotha, S.B., Alkhayal, Z., Mubaraki, S., et al. (2024) Artificial Intelligence in Dentistry: A Descriptive Review. Bioengineering, 11, Article 1267. https://doi.org/10.3390/bioengineering11121267
[43]
Sahoo, R.K., Sahoo, K.C., Dash, G.C., Kumar, G., Baliarsingh, S.K., Panda, B., et al. (2024) Diagnostic Performance of Artificial Intelligence in Detecting Oral Potentially Malignant Disorders and Oral Cancer Using Medical Diagnostic Imaging: A Systematic Review and Meta-Analysis. FrontiersinOralHealth, 5, Article 1491867. https://doi.org/10.3389/froh.2024.1494867
[44]
Al‐Buhaisi, D., Karami, S. and Gomaa, N. (2024) The Role of Teledentistry in Improving Oral Health Outcomes and Access to Dental Care: An Umbrella Review. JournalofOralRehabilitation, 51, 2375-2389. https://doi.org/10.1111/joor.13836
[45]
Migas, K., Kozłowski, R., Sierocka, A. and Marczak, M. (2022) Evaluation of Tele-Dentistry and Face-To-Face Appointments during the Provision of Dental Services in Poland. JournalofPersonalizedMedicine, 12, Article 1640. https://doi.org/10.3390/jpm12101640
[46]
Di Spirito, F., Amato, A., Di Palo, M.P., Ferraro, G.A., Baroni, A., Serpico, R., et al. (2022) COVID-19 Related Information on Pediatric Dental Care Including the Use of Teledentistry: A Narrative Review. Children, 9, Article 1942. https://doi.org/10.3390/children9121942
[47]
Soheili, F., Delfan, N., Masoudifar, N., Ebrahimni, S., Moshiri, B., Glogauer, M., et al. (2024) Toward Digital Periodontal Health: Recent Advances and Future Perspectives. Bioengineering, 11, Article 937. https://doi.org/10.3390/bioengineering11090937
[48]
Xu, J., Wang, L., Sun, H. and Liu, S. (2022) Evaluation of the Effect of Comprehensive Nursing Interventions on Plaque Control in Patients with Periodontal Disease in the Context of Artificial Intelligence. JournalofHealthcareEngineering, 2022, Article ID: 6505672. https://doi.org/10.1155/2022/6505672
[49]
Tsolakis, I.A., Gizani, S., Panayi, N., Antonopoulos, G. and Tsolakis, A.I. (2022) Three-dimensional Printing Technology in Orthodontics for Dental Models: A Systematic Review. Children, 9, Article 1106. https://doi.org/10.3390/children9081106
[50]
Chau, R.C.W., Thu, K.M., Chaurasia, A., Hsung, R.T.C. and Lam, W.Y. (2023) A Systematic Review of the Use of mHealth in Oral Health Education among Older Adults. DentistryJournal, 11, Article 189. https://doi.org/10.3390/dj11080189
[51]
Zolfaghari, M., Shirmohammadi, M., Shahhosseini, H., Mokhtaran, M. and Mohebbi, S.Z. (2021) Development and Evaluation of a Gamified Smart Phone Mobile Health Application for Oral Health Promotion in Early Childhood: A Randomized Controlled Trial. BMCOralHealth, 21, Article No. 18. https://doi.org/10.1186/s12903-020-01374-2
[52]
Shajari, S., Kuruvinashetti, K., Komeili, A. and Sundararaj, U. (2023) The Emergence of AI-Based Wearable Sensors for Digital Health Technology: A Review. Sensors, 23, Article 9498. https://doi.org/10.3390/s23239498
[53]
Shrivastava, R., Power, F., Tanwir, F., Feine, J. and Emami, E. (2019) University-Based Initiatives Towards Better Access to Oral Health Care for Rural and Remote Populations: A Scoping Review. PLOSONE, 14, e0217658. https://doi.org/10.1371/journal.pone.0217658
[54]
Feher, B., Tussie, C. and Giannobile, W.V. (2024) Applied Artificial Intelligence in Dentistry: Emerging Data Modalities and Modeling Approaches. Frontiers in Artificial Intelligence, 7, Article 1427517. https://doi.org/10.3389/frai.2024.1427517
[55]
Jeong, M., Radomski, K., Lopez, D., Liu, J.T., Lee, J.D. and Lee, S.J. (2023) Materials and Applications of 3D Printing Technology in Dentistry: An Overview. DentistryJournal, 12, Article 1. https://doi.org/10.3390/dj12010001
[56]
Maspero, C., Abate, A., Bellincioni, F., Cavagnetto, D., Lanteri, V., Costa, A., et al. (2019) Comparison of a Tridimensional Cephalometric Analysis Performed on 3T-MRI Compared with CBCT: A Pilot Study in Adults. ProgressinOrthodontics, 20, Article No. 40. https://doi.org/10.1186/s40510-019-0293-x
[57]
Mokhamed, T., Talib, M.A., Moufti, M.A., Abbas, S. and Khan, F. (2023) The Potential of Blockchain Technology in Dental Healthcare: A Literature Review. Sensors, 23, Article 3277. https://doi.org/10.3390/s23063277
[58]
Shen, N., Sequeira, L., Silver, M.P., et al. (2022) Patient and Provider Perspectives on Digital Health Tools for Preventive Care: An Integrated Review. JournalofMedicalInternetResearch, 24, e25407.
[59]
Joda, T., Waltimo, T., Probst-Hensch, N., Pauli-Magnus, C. and Zitzmann, N.U. (2019) Health Data in Dentistry: An Attempt to Master the Digital Challenge. PublicHealthGenomics, 22, 1-7. https://doi.org/10.1159/000501643
[60]
Saukkonen, P., Elovainio, M., Virtanen, L., Kaihlanen, A., Nadav, J., Lääveri, T., et al. (2022) The Interplay of Work, Digital Health Usage, and the Perceived Effects of Digitalization on Physicians’ Work: Network Analysis Approach. JournalofMedicalInternetResearch, 24, e38714. https://doi.org/10.2196/38714
[61]
Tudor Car, L., Poon, S., Kyaw, B.M., Cook, D.A., Ward, V., Atun, R., et al. (2022) Digital Education for Health Professionals: An Evidence Map, Conceptual Framework, and Research Agenda. JournalofMedicalInternetResearch, 24, e31977. https://doi.org/10.2196/31977
[62]
Maleki Varnosfaderani, S. and Forouzanfar, M. (2024) The Role of AI in Hospitals and Clinics: Transforming Healthcare in the 21st Century. Bioengineering, 11, Article 337. https://doi.org/10.3390/bioengineering11040337
[63]
Stoumpos, A.I., Kitsios, F. and Talias, M.A. (2023) Digital Transformation in Healthcare: Technology Acceptance and Its Applications. InternationalJournalofEnvironmentalResearchandPublicHealth, 20, Article 3407. https://doi.org/10.3390/ijerph20043407
[64]
Vodanović, M., Subašić, M., Milošević, D. and Savić Pavičin, I. (2023) Artificial Intelligence in Medicine and Dentistry. ActaStomatologicaCroatica, 57, 70-84. https://doi.org/10.15644/asc57/1/8
[65]
Jeste, D.V., Graham, S.A., Nguyen, T.T., Depp, C.A., Lee, E.E. and Kim, H. (2020) Beyond Artificial Intelligence: Exploring Artificial Wisdom. InternationalPsychogeriatrics, 32, 993-1001. https://doi.org/10.1017/s1041610220000927
[66]
Mehraeen, E., SeyedAlinaghi, S., Heydari, M., Karimi, A., Mahdavi, A., Mashoufi, M., et al. (2023) Telemedicine Technologies and Applications in the Era of COVID-19 Pandemic: A Systematic Review. HealthInformaticsJournal, 29, 24. https://doi.org/10.1177/14604582231167431
[67]
Shaver, N., Bennett, A., Beck, A., Skidmore, B., Traversy, G., Brouwers, M., et al. (2023) Health Equity Considerations in Guideline Development: A Rapid Scoping Review. CMAJOpen, 11, E357-E371. https://doi.org/10.9778/cmajo.20220130
[68]
Alsaleh, A. (2024) The Impact of Technological Advancement on Culture and Society. ScientificReports, 14, Article No. 32140. https://doi.org/10.1038/s41598-024-83995-z
[69]
Tian, Y. and Feng, C. (2023) How Does Internet Development Drive the Sustainable Economic Growth of China? Evidence from Internal-Structural Perspective of Green Total-Factor Productivity. ScienceoftheTotalEnvironment, 887, Article ID: 164125. https://doi.org/10.1016/j.scitotenv.2023.164125
[70]
Essén, A., Stern, A.D., Haase, C.B., Car, J., Greaves, F., Paparova, D., et al. (2022) Health App Policy: International Comparison of Nine Countries’ Approaches. NPJDigitalMedicine, 5, Article No. 31. https://doi.org/10.1038/s41746-022-00573-1
[71]
Obermeyer, Z., Powers, B., Vogeli, C. and Mullainathan, S. (2019) Dissecting Racial Bias in an Algorithm Used to Manage the Health of Populations. Science, 366, 447-453. https://doi.org/10.1126/science.aax2342
[72]
Cresswell, K.M., Sheikh, A. and Bates, D.W. (2017) Safety Risks of Health Information Technologies: Learning from Evidence and Experience. BMJQualityandSafety, 26, 529-531.
[73]
Ma, J., Schneider, L., Lapuschkin, S., Achtibat, R., Duchrau, M., Krois, J., et al. (2022) Towards Trustworthy AI in Dentistry. JournalofDentalResearch, 101, 1263-1268. https://doi.org/10.1177/00220345221106086
[74]
Rahim, A., Khatoon, R., Khan, T.A., Syed, K., Khan, I., Khalid, T., et al. (2024) Artificial Intelligence-Powered Dentistry: Probing the Potential, Challenges, and Ethicality of Artificial Intelligence in Dentistry. DigitalHealth, 10, 12. https://doi.org/10.1177/20552076241291345
[75]
Derruau, S., Bouchet, J., Nassif, A., Baudet, A., Yasukawa, K., Lorimier, S., et al. (2021) COVID-19 and Dentistry in 72 Questions: An Overview of the Literature. JournalofClinicalMedicine, 10, Article 779. https://doi.org/10.3390/jcm10040779
[76]
Shafi, I., Fatima, A., Afzal, H., Díez, I.d.l.T., Lipari, V., Breñosa, J., et al. (2023) A Comprehensive Review of Recent Advances in Artificial Intelligence for Dentistry E-health. Diagnostics, 13, Article 2196. https://doi.org/10.3390/diagnostics13132196
[77]
DaSilva, A.F., Robinson, M.A., Shi, W. and McCauley, L.K. (2022) The Forefront of Dentistry—Promising Tech-Innovations and New Treatments. JDRClinical&TranslationalResearch, 7, 16S-24S. https://doi.org/10.1177/23800844221116850
[78]
Pillai, S., Upadhyay, A., Khayambashi, P., Farooq, I., Sabri, H., Tarar, M., et al. (2021) Dental 3D-Printing: Transferring Art from the Laboratories to the Clinics. Polymers, 13, Article 157. https://doi.org/10.3390/polym13010157
[79]
Alyami, M.H. (2024) The Applications of 3d-Printing Technology in Prosthodontics: A Review of the Current Literature. Cureus, 16, e68501. https://doi.org/10.7759/cureus.68501
[80]
Woods, L., Dendere, R., Eden, R., Grantham, B., Krivit, J., Pearce, A., et al. (2023) Perceived Impact of Digital Health Maturity on Patient Experience, Population Health, Health Care Costs, and Provider Experience: Mixed Methods Case Study. JournalofMedicalInternetResearch, 25, e45868. https://doi.org/10.2196/45868
[81]
Krahe, M.A., Larkins, S.L. and Adams, N. (2024) Digital Health Implementation in Australia: A Scientometric Review of the Research. DigitalHealth, 10, 2. https://doi.org/10.1177/20552076241297729
[82]
Khatiwada, P., Yang, B., Lin, J. and Blobel, B. (2024) Patient-Generated Health Data (PGHD): Understanding, Requirements, Challenges, and Existing Techniques for Data Security and Privacy. JournalofPersonalizedMedicine, 14, Article 282. https://doi.org/10.3390/jpm14030282
[83]
Borges do Nascimento, I.J., Abdulazeem, H., Vasanthan, L.T., Martinez, E.Z., Zucoloto, M.L., Østengaard, L., et al. (2023) Barriers and Facilitators to Utilizing Digital Health Technologies by Healthcare Professionals. NPJDigitalMedicine, 6, Article No. 161. https://doi.org/10.1038/s41746-023-00899-4
[84]
Arias López, M.d.P., Ong, B.A., Borrat Frigola, X., Fernández, A.L., Hicklent, R.S., Obeles, A.J.T., et al. (2023) Digital Literacy as a New Determinant of Health: A Scoping Review. PLOSDigitalHealth, 2, e0000279. https://doi.org/10.1371/journal.pdig.0000279
[85]
Reddy, M., Shetty, S. and Vannala, V. (2019) Embracing Personalized Medicine in Dentistry. JournalofPharmacyandBioalliedSciences, 11, S92-S96. https://doi.org/10.4103/jpbs.jpbs_297_18
[86]
Reyes, L.T., Knorst, J.K., Ortiz, F.R. and Ardenghi, T.M. (2021) Scope and Challenges of Machine Learning-Based Diagnosis and Prognosis in Clinical Dentistry: A Literature Review. JournalofClinicalandTranslationalResearch, 7, 523-539.
[87]
Lee, J., Lee, T., Jung, H., Park, W. and Song, J.S. (2023) Effectiveness of an Oral Health Education Program Using a Smart Toothbrush with Quantitative Light-Induced Fluorescence Technology in Children. Children, 10, Article 429. https://doi.org/10.3390/children10030429
[88]
An, B.W., Shin, J.H., Kim, S., Kim, J., Ji, S., Park, J., et al. (2017) Smart Sensor Systems for Wearable Electronic Devices. Polymers, 9, Article 303. https://doi.org/10.3390/polym9080303
