Transforming telemedicine through predictive, preventive, and personalized medicine (PPPM): innovations, challenges, and future directions

Seewon R, Telemedicine. Opportunities and developments in member states: report on the second global survey on eHealth 2009 (Global Observatory for eHealth Series, 2). Healthc Inf Res. 2012;18(2):153–5. https://doi.org/10.4258/hir.2012.18.2.153

Article  Google Scholar 

Dorothy P, Roy P. Patient’s progress: Doctors and doctoring in eighteenth-century England. Choice Reviews Online 401 AD;27:27–4537. https://doi.org/10.5860/choice.27-4537

Thrall JH. Teleradiology. Part I. History and clinical applications. Radiol United States. 2007;243:613–7. https://doi.org/10.1148/radiol.2433070350.

Article  Google Scholar 

Strehle EM, Shabde N. One hundred years of telemedicine: does this new technology have a place in paediatrics? Arch Dis Child Engl. 2006;91:956–9. https://doi.org/10.1136/adc.2006.099622.

Article  CAS  Google Scholar 

Dietrich D, Dekova R, Davy S, Fahrni G, Geissbühler A. Applications of space technologies to global health: scoping review. J Med Internet Res Can. 2018;20:e230. https://doi.org/10.2196/jmir.9458.

Article  Google Scholar 

Lakshmi Priya R, Kumaraswamy V, Sunil NKB, Ramani S, Latha S, E-DigitTool:. A New-Fangled framework for disease prediction and diagnosis in remote healthcare applications. Iran J Sci Technol Trans Electr Eng. 2024;48:1463–81. https://doi.org/10.1007/s40998-024-00743-9.

Article  Google Scholar 

Stipa G, Gabbrielli F, Rabbito C, Di Lazzaro V, Amantini A, Grippo A, et al. The Italian technical/administrative recommendations for telemedicine in clinical neurophysiology. Neurol Sci Italy. 2021;42:1923–31. https://doi.org/10.1007/s10072-020-04732-8.

Article  CAS  Google Scholar 

Bai Y, Gu B, Tang C. Enhancing Real-Time patient monitoring in intensive care units with deep learning and the internet of Things. Big data. United States, 2025. https://doi.org/10.1089/big.2024.0113

Baker J, Stanley A. Telemedicine technology: a review of Services, Equipment, and other aspects. Curr Allergy Asthma Rep United States. 2018;18:60. https://doi.org/10.1007/s11882-018-0814-6.

Article  Google Scholar 

Belbase P, Bhusal R, Ghimire SS, Sharma S, Banskota B. Assuring assistance to healthcare and medicine: internet of things, artificial intelligence, and artificial intelligence of things. Front Artif Intell. 2024;7:1442254. https://doi.org/10.3389/frai.2024.1442254.

Article  PubMed  PubMed Central  Google Scholar 

Hare N, Bansal P, Bajowala SS, Abramson SL, Chervinskiy S, Corriel R, et al. Work group report: COVID-19: unmasking telemedicine. J Allergy Clin Immunol Pract United States. 2020;8:2461–e24733. https://doi.org/10.1016/j.jaip.2020.06.038.

Article  Google Scholar 

Tan LO, Ganapathy S. A single centre study of the level of parents’ satisfaction with the COVID-19 telemedicine consultation. Eur J Pediatr Ger. 2024;183:213–8. https://doi.org/10.1007/s00431-023-05276-7.

Article  Google Scholar 

Kiani SN, Cho LD, Poeran J, Wilson L, Zhong H, Mazumdar M, et al. Musculoskeletal telemedicine trends preceding the COVID-19 pandemic and potential implications of rapid telemedicine expansion. Int J Telemed Appl United States. 2023;2023:9900145. https://doi.org/10.1155/2023/9900145.

Article  Google Scholar 

Dowling RA, Zhang S, Goldfischer E, Albala DM, Bart A. Telemedicine utilization in the COVID-19 era: patterns of care in community urology practice. Urol Pract United States. 2024;11:474–85. https://doi.org/10.1097/UPJ.0000000000000523.

Article  Google Scholar 

Golubnitschaja O, Costigliola V. General report & recommendations in predictive, preventive and personalised medicine 2012: white paper of the European association for Predictive, preventive and personalised medicine. EPMA J. 2012;3:14. https://doi.org/10.1186/1878-5085-3-14.

Article  PubMed  PubMed Central  Google Scholar 

Tufail M, Hu J-J, Liang J, He C-Y, Wan W-D, Huang Y-Q, et al. Predictive, preventive, and personalized medicine in breast cancer: targeting the PI3K pathway. J Transl Med. 2024;22:15. https://doi.org/10.1186/s12967-023-04841-w

Article  CAS  PubMed  PubMed Central  Google Scholar 

Bo RK, Tae KY, Hoon YK, Ik HR, Jin KK, In SL, et al. Oculomics for sarcopenia prediction: a machine learning approach toward predictive, preventive, and personalized medicine. EPMA J. 2022;13:367–82. https://doi.org/10.1007/s13167-022-00292-3

Article  Google Scholar 

Mohd Faizal AS, Thevarajah TM, Khor SM, Chang S-W. A review of risk prediction models in cardiovascular disease: conventional approach vs. artificial intelligent approach. Comput Methods Programs Biomed. 2021;207:106190. https://doi.org/10.1016/j.cmpb.2021.106190.

Article  PubMed  Google Scholar 

Vogel VG. Follow-up of the breast cancer prevention trial and the future of breast cancer prevention efforts. Clin Cancer Res. 2001;7:s4413–8. s; discussion 4411s-4412s.

Google Scholar 

Nannan Panday RS, Minderhoud TC, Alam N, Nanayakkara PWB. Prognostic value of early warning scores in the emergency department (ED) and acute medical unit (AMU): A narrative review. Eur J Intern Med. 2017;45:20–31. https://doi.org/10.1016/j.ejim.2017.09.027.

Article  CAS  PubMed  Google Scholar 

Jain N, Nagaich U, Pandey M, Chellappan DK, Dua K. Predictive genomic tools in disease stratification and targeted prevention: a recent update in personalized therapy advancements. EPMA J. 2022;13:561–80. https://doi.org/10.1007/s13167-022-00304-2.

Article  PubMed  PubMed Central  Google Scholar 

Zhang Q, Wang N, Rui Y, Xia Y, Xiong S, Xia X. New insight of metabolomics in ocular diseases in the context of 3P medicine. EPMA J. 2023;14:53–71. https://doi.org/10.1007/s13167-023-00313-9.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Winters S, Martin C, Murphy D, Shokar NK. Breast cancer Epidemiology, Prevention, and screening. Prog Mol Biol Transl Sci. 2017;151:1–32. https://doi.org/10.1016/bs.pmbts.2017.07.002.

Article  CAS  PubMed  Google Scholar 

Dong Z, Li P, Jiang Y, Wang Z, Fu S, Che H, et al. Integrative Multi-Omics and routine blood analysis using deep learning: Cost-Effective early prediction of chronic disease risks. Adv Sci (Weinh). 2025;12:e2412775. https://doi.org/10.1002/advs.202412775.

Article  PubMed  PubMed Central  Google Scholar 

Karpiel I, Mysiński M, Olesz K, Czerw M. Overview of respiratory sensor solutions to support patient diagnosis and monitoring. Sens (Basel). 2025;25:1078. https://doi.org/10.3390/s25041078.

Article  Google Scholar 

Sabanayagam C, Xu D, Ting DSW, Nusinovici S, Banu R, Hamzah H, et al. A deep learning algorithm to detect chronic kidney disease from retinal photographs in community-based populations. Lancet Digit Health. 2020;2:e295–302. https://doi.org/10.1016/S2589-7500(20)30063-7.

Article  PubMed  Google Scholar 

Long E, Chen J, Wu X, Liu Z, Wang L, Jiang J, et al. Artificial intelligence manages congenital cataract with individualized prediction and telehealth computing. NPJ Digit Med. 2020;3:112. https://doi.org/10.1038/s41746-020-00319-x.

Article  PubMed  PubMed Central  Google Scholar 

Muhammad Usman S, Khalid S, Bashir S. A deep learning based ensemble learning method for epileptic seizure prediction. Comput Biol Med. 2021;136:104710. https://doi.org/10.1016/j.compbiomed.2021.104710.

Article  PubMed  Google Scholar 

Shen J, Ghatti S, Levkov NR, Shen H, Sen T, Rheuban K, et al. A survey of COVID-19 detection and prediction approaches using mobile devices, AI, and telemedicine. Front Artif Intell. 2022;5:1034732. https://doi.org/10.3389/frai.2022.1034732.

Article  PubMed  PubMed Central  Google Scholar 

Wu C, Restrepo D, Nakayama LF, Zago Ribeiro L, Shuai Z, Barboza NS, et al. A portable retina fundus photos dataset for clinical, demographic, and diabetic retinopathy prediction. Sci Data. 2025;12:323. https://doi.org/10.1038/s41597-025-04627-3.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Terefe FT, Yang B, Jemal K, Ayana D, Adefris M, Awol M, et al. Advancing antenatal care in ethiopia: the impact of Tele-Ultrasound on antenatal ultrasound access in rural Ethiopia. Telemed J E Health. 2025;31:85–93. https://doi.org/10.1089/tmj.2024.0066.

Article  PubMed  Google Scholar 

Pena J, González-Castaño DM, Gómez F, Gago-Arias A, González-Castaño FJ, Rodríguez-Silva D, et al. eIMRT: a web platform for the verification and optimization of radiation treatment plans. J Appl Clin Med Phys. 2009;10:205–20. https://doi.org/10.1120/jacmp.v10i3.2998.

Article  PubMed  PubMed Central  Google Scholar 

Bhatt P, Liu J, Gong Y, Wang J, Guo Y. Emerging artificial Intelligence-Empowered mHealth: scoping review. JMIR Mhealth Uhealth. 2022;10:e35053. https://doi.org/10.2196/35053.

Article  PubMed 

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