Digital twins to personalize medicine

Network medicine: a network-based approach to human disease

Barabási, A.-L., Gulbahce, N., & Loscalzo, J. (2011) · Nature Reviews Genetics · doi:10.1038/nrg2918 · Cited by 5,034

Intra- and Inter-cellular Rewiring of the Human Colon during Ulcerative Colitis

Smillie, C. S., Biton, M., Ordovás-Montañés, J., Sullivan, K. M., Burgin, G., Graham, D. B., Herbst, R. H., Rogel, N., Slyper, M., Waldman, J., et al. (2019) · Cell · doi:10.1016/j.cell.2019.06.029 · Cited by 1,417

Deep learning: new computational modelling techniques for genomics

Eraslan, G., Avsec, Ž., Gagneur, J., & Theis, F. J. (2019) · Nature Reviews Genetics · doi:10.1038/s41576-019-0122-6 · Cited by 1,288

Make more digital twins

Tao, F., & Qi, Q. (2019) · Nature · doi:10.1038/d41586-019-02849-1 · Cited by 799

Human symptoms–disease network

Zhou, X., Menche, J., Barabási, A.-Ĺ., & Sharma, A. (2014) · Nature Communications · doi:10.1038/ncomms5212 · Cited by 659

Single-cell analyses to tailor treatments

Shalek, A. K., & Benson, M. (2017) · Science Translational Medicine · doi:10.1126/scitranslmed.aan4730 · Cited by 163

A decade of digital medicine innovation

Topol, E. J. (2019) · Science Translational Medicine · doi:10.1126/scitranslmed.aaw7610 · Cited by 117

A validated single-cell-based strategy to identify diagnostic and therapeutic targets in complex diseases

Gawel, D. R., Serra-Musach, J., Lilja, S., Aagesen, J., Arenas, À., Asking, B., Bengnér, M., Björkander, J., Biggs, S., Ernerudh, J., et al. (2019) · Genome Medicine · doi:10.1186/s13073-019-0657-3 · Cited by 95

A validated gene regulatory network and GWAS identifies early regulators of T cell–associated diseases

Gustafsson, M., Gawel, D. R., Alfredsson, L. S., Baranzini, S. E., Björkander, J., Blomgran, R., Hellberg, S., Eklund, D., Ernerudh, J., Kockum, I. S., et al. (2015) · Science Translational Medicine · doi:10.1126/scitranslmed.aad2722 · Cited by 67

Utilization of precision medicine digital twins for drug discovery in Alzheimer's disease

Ren, Y., Pieper, A. A., & Cheng, F. (2025) · Neurotherapeutics · doi:10.1016/j.neurot.2025.e00553 · Cited by 48

The Impact of Healthcare 4.0 on the Healthcare Service Quality: A Systematic Literature Review

Sony, M., Antony, J., & McDermott, O. (2022) · Hospital Topics · doi:10.1080/00185868.2022.2048220 · Cited by 42

Artificial intelligence in cancer research: learning at different levels of data granularity

Cirillo, D., Núñez‐Carpintero, I., & Valencia, A. (2021) · Molecular Oncology · doi:10.1002/1878-0261.12920 · Cited by 45

Computational methods and biomarker discovery strategies for spatial proteomics: a review in immuno-oncology

Mi, H., Sivagnanam, S., Ho, W. J., Zhang, S., Bergman, D. R., Deshpande, A. M., Baras, A. S., Jaffee, E. M., Coussens, L. M., Fertig, E. J., et al. (2024) · Briefings in Bioinformatics · doi:10.1093/bib/bbae421 · Cited by 38

Sports related concussion: an emerging era in digital sports technology

Powell, D., Stuart, S., & Godfrey, A. (2021) · npj Digital Medicine · doi:10.1038/s41746-021-00538-w · Cited by 36

Longitudinal big biological data in the AI era

Mardinoğlu, A., Türkez, H., Shong, M., Srinivasulu, V. P., Nielsen, J., Palsson, B. Ø., Hood, L., & Uhlén, M. (2025) · Molecular Systems Biology · doi:10.1038/s44320-025-00134-0 · Cited by 36

A virtual host model of Mycobacterium tuberculosis infection identifies early immune events as predictive of infection outcomes

Joslyn, L. R., Linderman, J. J., & Kirschner, D. E. (2022) · Journal of Theoretical Biology · doi:10.1016/j.jtbi.2022.111042 · Cited by 36

What Is a Digital Twin? Experimental Design for a Data-Centric Machine Learning Perspective in Health

Emmert‐Streib, F., & Yli-Harja, O. P. (2022) · International Journal of Molecular Sciences · doi:10.3390/ijms232113149 · Cited by 38

Privacy and Security Issues for Human Digital Twins

Sirigu, G., Carminati, B., & Ferrari, E. (2022) · IEEE International Conference on Trust, Privacy and Security in Intelligent Systems and Applications (TPS-ISA) · doi:10.1109/tps-isa56441.2022.00011 · Cited by 35

Distributed and trustworthy digital twin platform based on blockchain and Web3 technologies

Bamakan, S. M. H., & Far, S. B. (2024) · Cyber Security and Applications · doi:10.1016/j.csa.2024.100064 · Cited by 36

The materials tetrahedron has a “digital twin”

Deagen, M. E., Brinson, L. C., Vaia, R. A., & Schadler, L. S. (2022) · MRS Bulletin · doi:10.1557/s43577-021-00214-0 · Cited by 34

A digital twin model for evidence-based clinical decision support in multiple myeloma treatment

Grieb, N., Schmierer, L., Kim, H. U., Strobel, S., Schulz, C., Meschke, T., Kubasch, A. S., Brioli, A., Platzbecker, U., Neumuth, T., et al. (2023) · Frontiers in Digital Health · doi:10.3389/fdgth.2023.1324453 · Cited by 32

AI and innovation in clinical trials

Badani, A., de Moraes, F. Y., Vollmuth, P., Chung, C. D., & Mansouri, A. (2025) · npj Digital Medicine · doi:10.1038/s41746-025-02048-5 · Cited by 33

Epistemic Rights and Responsibilities of Digital Simulacra for Biomedicine

Cho, M. K., & Martinez‐Martin, N. (2022) · The American Journal of Bioethics · doi:10.1080/15265161.2022.2146785 · Cited by 32

Technologies, Applications, and Challenges of Digital Twin Across Industries: A Systematic Review of the State-of-the-Art Literature

Bae, C.-H., Choi, E.-T., & Lee, S. (2025) · IEEE Access · doi:10.1109/access.2025.3601615 · Cited by 40

The Use of Smart Rings in Health Monitoring—A Meta-Analysis

Fiore, M., Bianconi, A., Sicari, G., Conni, A., Lenzi, J., Tomaiuolo, G., Zito, F., Golinelli, D., & Sanmarchi, F. (2024) · Applied Sciences · doi:10.3390/app142310778 · Cited by 37

Transformative roles of digital twins from drug discovery to continuous manufacturing: pharmaceutical and biopharmaceutical perspectives

Maharjan, R., Kim, N. A., Kim, K. H., & Jeong, S. H. (2025) · International Journal of Pharmaceutics X · doi:10.1016/j.ijpx.2025.100409 · Cited by 30

Digital Twins for Predictive, Preventive Personalized, and Participatory Treatment of Immune-Mediated Diseases

Benson, M. (2023) · Arteriosclerosis Thrombosis and Vascular Biology · doi:10.1161/atvbaha.122.318331 · Cited by 29

Lung cancer multi-omics digital human avatars for integrating precision medicine into clinical practice: the LANTERN study

Lococo, F., Boldrini, L., Charles-Davies, D., Evangelista, J., Nero, C., Flamini, S., Minucci, A., Paolis, E. D., Vita, E., Cesario, A., et al. (2023) · BMC Cancer · doi:10.1186/s12885-023-10997-x · Cited by 29

A Real-Time Cross-Domain Wi-Fi-Based Gesture Recognition System for Digital Twins

Su, J. D., Mao, Q., Liao, Z., Sheng, Z., Huang, C., & Zhang, X. (2023) · IEEE Journal on Selected Areas in Communications · doi:10.1109/jsac.2023.3310073 · Cited by 28

Electronic medical records as a source of real-world clinical data

Gusev, A. V., Zingerman, B. V., Тюфилин, Д. С., & Zinchenko, V. V. (2022) · Real-World Data & Evidence · doi:10.37489/2782-3784-myrwd-13 · Cited by 28

Using Digital Twins for Precision Medicine in Vascular Surgery

Lareyre, F., Adam, C., Carrier, M., & Raffort, J. (2020) · Annals of Vascular Surgery · doi:10.1016/j.avsg.2020.04.042 · Cited by 27

Analyzing the Scholarly Literature of Digital Twin Research: Trends, Topics and Structure

Emmert‐Streib, F., Tripathi, S., & Dehmer, M. (2023) · IEEE Access · doi:10.1109/access.2023.3290488 · Cited by 27

Using Constrained-Disorder Principle-Based Systems to Improve the Performance of Digital Twins in Biological Systems

Sigawi, T., & Ilan, Y. (2023) · Biomimetics · doi:10.3390/biomimetics8040359 · Cited by 27

Math, magnets, and medicine: enabling personalized oncology

Hormuth, D. A., Jarrett, A. M., Lorenzo, G., Lima, E. A. B. F., Wu, C., Chung, C. D., Patt, D. A., & Yankeelov, T. E. (2021) · Expert Review of Precision Medicine and Drug Development · doi:10.1080/23808993.2021.1878023 · Cited by 27

Architecture designing of digital twin in a healthcare unit

Noeikham, P., Buakum, D., & Sirivongpaisal, N. (2024) · Health Informatics Journal · doi:10.1177/14604582241296792 · Cited by 26

Digital Representation of Patients as Medical Digital Twins: Data-Centric Viewpoint

Demuth, S., Seze, J. D., Edan, G., Ziemssen, T., Simon, F., & Gourraud, P. (2025) · JMIR Medical Informatics · doi:10.2196/53542 · Cited by 26

A Scoping Review of Digital Twins in the Context of the Covid-19 Pandemic

Khan, A., Milne‐Ives, M., Meinert, E., Iyawa, G. E., Jones, R. B., & Josephraj, A. N. (2022) · Biomedical Engineering and Computational Biology · doi:10.1177/11795972221102115 · Cited by 26

Digital twins in healthcare and biomedicine

Subaşı, A., & Subasi, M. E. (2024) · Elsevier eBooks · doi:10.1016/b978-0-443-21598-8.00011-7 · Cited by 26

Digital Twins Use in Plastic Surgery: A Systematic Review

Seth, I., Lim, B., Lu, P. Y. J., Xie, Y., Cuomo, R., Ng, S., Rozen, W. M., & Sofiadellis, F. (2024) · Journal of Clinical Medicine · doi:10.3390/jcm13247861 · Cited by 24

Predictive modeling in neurocritical care using causal artificial intelligence

Dang, J., Lal, A., Flurin, L., James, A., Gajic, O., & Rabinstein, A. A. (2021) · World Journal of Critical Care Medicine · doi:10.5492/wjccm.v10.i4.112 · Cited by 24

Applications of Multimodal Artificial Intelligence in Non-Hodgkin Lymphoma B Cells

Isavand, P., Aghamiri, S. S., & Amin, R. (2024) · Biomedicines · doi:10.3390/biomedicines12081753 · Cited by 24

Digital twins elucidate critical role of Tscm in clinical persistence of TCR-engineered cell therapy

Joslyn, L. R., Huang, W., Miles, D., Hosseini, I., & Ramanujan, S. (2024) · npj Systems Biology and Applications · doi:10.1038/s41540-024-00335-7 · Cited by 24

Digital twin in healthcare: Classification and typology of models based on hierarchy, application, and maturity

Maïzi, Y., Arcand, A., & Bendavid, Y. (2024) · Internet of Things · doi:10.1016/j.iot.2024.101379 · Cited by 23

Building a modular and multi-cellular virtual twin of the synovial joint in Rheumatoid Arthritis

Zerrouk, N., Augé, F., & Niarakis, A. (2024) · npj Digital Medicine · doi:10.1038/s41746-024-01396-y · Cited by 23

Importance of Prospective Registries and Clinical Research Networks in the Evolution of Spinal Cord Injury Care

Kelly-Hedrick, M., Abd‐El‐Barr, M. M., Aarabi, B., Curt, A. E. P., Howley, S. P., Harrop, J. S., Kirshblum, S., Neal, C. J., Noonan, V. K., Park, C., et al. (2022) · Journal of Neurotrauma · doi:10.1089/neu.2022.0450 · Cited by 24

Toward the Internet of Medical Things: Architecture, trends and challenges

Niu, Q., Li, H., Liu, Y., Qin, Z., Zhang, L., Chen, J., & Lv, Z. (2023) · Mathematical Biosciences & Engineering · doi:10.3934/mbe.2024028 · Cited by 27

A systematic review of Digital Twins in efficient pandemic management with challenges and emerging trends

Eumi, E. M. (2024) · Decision Analytics Journal · doi:10.1016/j.dajour.2024.100502 · Cited by 17

E‐waste: mechanisms of toxicity and safety testing

Eze, C. T., & Vinken, M. (2024) · FEBS Open Bio · doi:10.1002/2211-5463.13863 · Cited by 22

Digital twins and the ethics of health decision-making concerning children

Braun, M., & Krutzinna, J. I. (2022) · Patterns · doi:10.1016/j.patter.2022.100469 · Cited by 22

CONNECTED: leveraging digital twins and personal knowledge graphs in healthcare digitalization

Carbonaro, A., Marfoglia, A., Nardini, F., & Mellone, S. (2023) · Frontiers in Digital Health · doi:10.3389/fdgth.2023.1322428 · Cited by 22

Control of medical digital twins with artificial neural networks

Böttcher, L., Fonseca, L. L., & Laubenbacher, R. (2025) · Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences · doi:10.1098/rsta.2024.0228 · Cited by 21

Digital twins for personalized treatment in uro-oncology in the era of artificial intelligence

Görtz, M., Brandl, C., Nitschke, A., Riediger, A. L., Stromer, D., Byczkowski, M., Heuveline, V., & Weidemüller, M. (2025) · Nature Reviews Urology · doi:10.1038/s41585-025-01096-6 · Cited by 23

Life Course Digital Twins–Intelligent Monitoring for Early and Continuous Intervention and Prevention (LifeTIME): Proposal for a Retrospective Cohort Study

Milne‐Ives, M., Fraser, L., Khan, A., Walker, D. J., van Velthoven, M. H., May, J., Wolfe, I., Harding, T., & Meinert, E. (2022) · JMIR Research Protocols · doi:10.2196/35738 · Cited by 23

Routine omics collection is a golden opportunity for European human research in space and analog environments

Cope, H., Willis, C. R. G., MacKay, M. J., Rutter, L. A., Toh, L. S., Williams, P. M., Herranz, R., Borg, J., Bezdan, D., Giacomello, S., et al. (2022) · Patterns · doi:10.1016/j.patter.2022.100550 · Cited by 21

AI-produced certainties in health care: current and future challenges

Tretter, M., Ott, T., & Dabrock, P. (2023) · AI and Ethics · doi:10.1007/s43681-023-00374-6 · Cited by 21

Embracing the future of medicine with virtual patients

Wang, K., Parrott, N. J., & Lavé, T. (2025) · Drug Discovery Today · doi:10.1016/j.drudis.2025.104322 · Cited by 20

Cytotoxicity - Understanding Cellular Damage and Response

Sukumaran, A., & Mansour, M. A. (2022) · IntechOpen eBooks · doi:10.5772/intechopen.100956 · Cited by 22

scDrugPrio: a framework for the analysis of single-cell transcriptomics to address multiple problems in precision medicine in immune-mediated inflammatory diseases

Schäfer, S., Smelik, M., Sysoev, O., Zhao, Y., Eklund, D., Lilja, S., Gustafsson, M., Heyn, H., Julià, A., Kovács, I. A., et al. (2024) · Genome Medicine · doi:10.1186/s13073-024-01314-7 · Cited by 20

Sensing the Future of Thrombosis Management: Integrating Vessel-on-a-Chip Models, Advanced Biosensors, and AI-Driven Digital Twins

Zhao, Y. C., Wang, Z., Zhao, H., Yap, N. A., Wang, R., Cheng, W., Xu, X., & Ju, L. A. (2025) · ACS Sensors · doi:10.1021/acssensors.4c02764 · Cited by 20

Digital twins for accelerating drug discovery and development: opportunities and challenges

Venkatapurapu, S. P., Clegg, L. E., Nowojewski, A., Kimko, H. H. C., Olabode, D., Sawant‐Basak, A., & Vishwanathan, K. (2026) · Drug Discovery Today · doi:10.1016/j.drudis.2026.104617 · Cited by 19

Combining experimental and computational techniques to understand and improve dry powder inhalers

Chaugule, V., Wong, C. Y. J., Inthavong, K., Fletcher, D. F., Young, P. M., Soria, J., & Traini, D. (2022) · Expert Opinion on Drug Delivery · doi:10.1080/17425247.2022.2026922 · Cited by 19

Measuring pain and nociception: Through the glasses of a computational scientist. Transdisciplinary overview of methods

Kutafina, E., Becker, S., & Namer, B. (2023) · Frontiers in Network Physiology · doi:10.3389/fnetp.2023.1099282 · Cited by 19

Ethical and quality of care–related challenges of digital health twins in care settings for older adults: scoping review

Jabin, M. S. R., Mirza, A., Ilodibe, A., Eldabi, T., & Vann Yaroson, E. (2025) · JMIR Aging · doi:10.2196/73925 · Cited by 18

Advancing Sustainable Cyber-Physical System Development with a Digital Twins and Language Engineering Approach: Smart Greenhouse Applications

Subahi, A. F. (2024) · Technologies · doi:10.3390/technologies12090147 · Cited by 18

The X-Age Project to construct a Chinese aging clock

Li, J., Jiang, M., Wang, Q., Zheng, Z., Shen, J., Li, J., Xiong, M., Zheng, Y., Lu, X., Cai, Y., et al. (2025) · Nature Aging · doi:10.1038/s43587-025-00935-w · Cited by 19

Digital twins in dosimetry and radiotherapy, a survey and some applications

Sumini, M., Teodori, F., & Isolan, L. (2024) · Radiation Physics and Chemistry · doi:10.1016/j.radphyschem.2024.111649 · Cited by 18

From Multiscale Biophysics to Digital Twins of Tissues and Organs: Future Opportunities for in-silico Pharmacology

Barros, M. T., Paci, M., Tervonen, A., Passini, E., Koivumäki, J. T., Hyttinen, J., & Lenk, K. (2024) · IEEE Transactions on Molecular Biological and Multi-Scale Communications · doi:10.1109/tmbmc.2024.3442083 · Cited by 18

Emerging Treatments for Disorders of Consciousness in Paediatric Age

Irzan, H., Pozzi, M., Chikhladze, N., Cebanu, S., Tadevosyan, A. E., Cornelia, C., Tsiskaridze, A., Melbourne, A., Strazzer, S., Marc Modat, A., et al. (2022) · Brain Sciences · doi:10.3390/brainsci12020198 · Cited by 18

Wearable Devices and Health Monitoring

Kanakaprabha, S., Kumar, G. G., Reddy, B. P., Raju, Y. R., & Rai, P. C. M. (2024) · Wiley eBooks · doi:10.1002/9781394270910.ch12 · Cited by 18

Trends in Mental Health Outcomes of College Students Amid the Pandemic (Roadmap mHealth App): Longitudinal Observational Study

Jayaraj, G., Cao, X., Horwitz, A. G., Rozwadowski, M., Shea, S., Hanauer, S. N., Hanauer, D. A., Tewari, M., Shedden, K., & Choi, S. W. (2024) · Journal of Medical Internet Research · doi:10.2196/67627 · Cited by 21

Toward Intelligent AIoT: A Comprehensive Survey on Digital Twin and Multimodal Generative AI Integration

Luo, X., Wang, A., Zhang, X., Huang, K., Wang, S., Chen, L., & Cui, Y. (2025) · Mathematics · doi:10.3390/math13213382 · Cited by 19

Organoids: A new frontier in precision medicine and engineering

Gao, Q., Wu, Y., Mao, Y., Chen, X., Geng, Z., & Su, J. (2025) · Precision medicine and engineering. · doi:10.1016/j.preme.2025.100049 · Cited by 17

A roadmap for delivering a human musculoskeletal cell atlas

Baldwin, M. J., Buckley, C. D., Guilak, F., Hulley, P. A., Cribbs, A. P., & Snelling, S. J. B. (2023) · Nature Reviews Rheumatology · doi:10.1038/s41584-023-01031-2 · Cited by 17

Rapid Progress in Intelligent Radiotherapy and Future Implementation

Chen, G., Cui, J., Qian, J., Zhu, J., Zhao, L., Luo, B., Cui, T., Zhong, L., Yang, F., Yang, G., et al. (2022) · Cancer Investigation · doi:10.1080/07357907.2022.2044842 · Cited by 17

The Anti-Leukemia Effect of Ascorbic Acid: From the Pro-Oxidant Potential to the Epigenetic Role in Acute Myeloid Leukemia

Travaglini, S., Gurnari, C., Antonelli, S., Silvestrini, G., Noguera, N. I., Ottone, T., & Voso, M. T. (2022) · Frontiers in Cell and Developmental Biology · doi:10.3389/fcell.2022.930205 · Cited by 18

Personalized Risk Schemes and Machine Learning to Empower Genomic Prognostication Models in Myelodysplastic Syndromes

Awada, H., Gurnari, C., Durmaz, A., Awada, H. K., Pagliuca, S., & Visconte, V. (2022) · International Journal of Molecular Sciences · doi:10.3390/ijms23052802 · Cited by 16

Digital Twins in Healthcare: an Assessment of Technological and Practical Prospects

Kobyakova, О. S., Стародубов, В. И., Kurakova, N. G., & Цветкова, Л. А. (2021) · Annals of the Russian academy of medical sciences · doi:10.15690/vramn1717 · Cited by 16

Modeling a simulated Forest to get Burning Times of Tree Species using a Digital Twin

Sanchez-Guzman, G., Velásquez, W., & Alvarez‐Alvarado, M. S. (2022) · IEEE Annual Computing and Communication Workshop and Conference (CCWC) · doi:10.1109/ccwc54503.2022.9720768 · Cited by 16

Modeling signaling pathways in biology with MaBoSS: From one single cell to a dynamic population of heterogeneous interacting cells

Calzone, L., Noël, V., Barillot, E., Kroemer, G., & Stoll, G. (2022) · Computational and Structural Biotechnology Journal · doi:10.1016/j.csbj.2022.10.003 · Cited by 15

Artificial Intelligence for Predictive Modeling in CRISPR/Cas9 Gene Editing: a Survey of Methods and Design Strategies

Patel, J., Patel, D. K., & Raval, A. S. (2025) · The Journal of Gene Medicine · doi:10.1002/jgm.70061 · Cited by 15

Enabling Precision Medicine via Contemporary and Future Communication Technologies: A Survey

Chude-Okonkwo, U. A. K., Paul, B. S., & Vasilakos, A. V. (2022) · IEEE Access · doi:10.1109/access.2022.3175573 · Cited by 15

Is digital sovereignty normatively desirable?

Braun, M., & Hummel, P. (2024) · Information Communication & Society · doi:10.1080/1369118x.2024.2332624 · Cited by 15

Digital chemistry: navigating the confluence of computation and experimentation – definition, status quo, and future perspective

Bräse, S. (2024) · Digital Discovery · doi:10.1039/d4dd00130c · Cited by 15

The Digital Twin: Modular Model-Based Approach to Personalized Medicine

Gaebel, J., Keller, J., Schneider, D., Lindenmeyer, A., Neumuth, T., & Franke, S. (2021) · Current Directions in Biomedical Engineering · doi:10.1515/cdbme-2021-2057 · Cited by 15

Leveraging artificial intelligence and machine learning for unraveling pathogenesis and advancing precision medicine in autoimmune diseases

Cao, C., Zhao, W., Guo, J., Wang, Z., Lü, A., & Liang, C. C. (2025) · The Innovation Medicine · doi:10.59717/j.xinn-med.2025.100154 · Cited by 14

Digital Twins in Pediatric Infectious Diseases: Virtual Models for Personalized Management

Esposito, S., Campana, B. R., Seferi, H., Cinti, E., & Argentiero, A. (2025) · Journal of Personalized Medicine · doi:10.3390/jpm15110514 · Cited by 16

Applying Artificial Intelligence and machine learning in precision nutrition

Massara, P., Kirkland, J., Pagani, I., Huey, S. L., Hirsh, H., McDonald, D. T., Patel, L., Finkelstein, J. L., Gantz, M. G., Wang, F., et al. (2026) · Nature Communications · doi:10.1038/s41467-026-75004-w · Cited by 15

Artificial Intelligence-Aided Digital Twin Design: A Systematic ReviewPreprint

Hao, N., Li, Y., Liu, K., Liu, S., Lu, Y., Xu, B., Li, C., Chen, J., Yue, L., Fu, T., et al. (2024) · Preprints.org · doi:10.20944/preprints202408.2063.v1 · Cited by 16

Artificial intelligence in myeloid malignancies: Clinical applications of machine learning in myelodysplastic syndromes and acute myeloid Leukemia

Al‐Nusair, J., Lanino, L., Durmaz, A., Porta, M. G. D., Zeidan, A. M., & Kewan, T. Z. (2025) · Blood Reviews · doi:10.1016/j.blre.2025.101340 · Cited by 13

Simulated misuse of large language models and clinical credit systems

Anibal, J., Huth, H. B., Gunkel, J., Gregurick, S. K., & Wood, B. J. (2024) · npj Digital Medicine · doi:10.1038/s41746-024-01306-2 · Cited by 13

Exploration of an adaptive proton therapy strategy using CBCT with the concept of digital twins

Chang, C., Tian, Z., Qiu, R. L. J., McGinnis, H. S., Bohannon, D. H., Patel, P. R., Wang, Y., Yu, D. S., Patel, S. A., Zhou, J., et al. (2025) · Physics in Medicine and Biology · doi:10.1088/1361-6560/ada684 · Cited by 13

Network-Based Approaches for Drug Target Identification

Koutsandreas, T., Tsafou, K., Horn, H., Barrett, I. P., & Petsalaki, E. (2025) · Annual Review of Biomedical Data Science · doi:10.1146/annurev-biodatasci-101424-120950 · Cited by 14

Challenging gold standard hematology diagnostics through the introduction of whole genome sequencing and artificial intelligence

Haferlach, T., & Walter, W. (2023) · International Journal of Laboratory Hematology · doi:10.1111/ijlh.14033 · Cited by 13

A framework for digital twin integration in biofabrication and a scaffold 3D bioplotting case study

Ahmed, N., Narayanan, L. K., & Shirwaiker, R. A. (2024) · Manufacturing Letters · doi:10.1016/j.mfglet.2024.09.144 · Cited by 13

Development of a Digital Twin Framework for a PV System to Resolve Partial Shading

Bavithra, K., Ramasamy, L., Stonier, A. A., & Sathiasamuel, C. R. (2024) · Mathematical Problems in Engineering · doi:10.1155/2024/8374487 · Cited by 14

Convergence of Integrated Sensing and Communication (ISAC) and Digital-Twin Technologies in Healthcare Systems: A Comprehensive Review

Kim, Y., Oh, S., & Kim, G. (2025) · Signals · doi:10.3390/signals6040051 · Cited by 12

COBREXA.jl: constraint-based reconstruction and exascale analysis

Kratochvíl, M., Heirendt, L., Wilken, S. E., Pusa, T., Arreckx, S., Noronha, A., van Aalst, M., Satagopam, V., Ebenhöh, O., Schneider, R., et al. (2021) · Bioinformatics · doi:10.1093/bioinformatics/btab782 · Cited by 12

Using constrained-disorder principle-based systems to improve the performance of digital twins in biological systems (Preprint)Preprint

Sigawi, T., & Ilan, Y. (2023) · doi:10.2196/preprints.46304 · Cited by 12

Digital twins for children with rare diseases: an exploration of the legal and ethical issues

März, J. W., Baumgartner, M., Blau, N., & Biller‐Andorno, N. (2025) · Ethics and Information Technology · doi:10.1007/s10676-025-09848-z · Cited by 11

Artificial intelligence in modern clinical practice

Galiana, L. I., Martin, F., & Espinosa, P. (2025) · Medical Research Archives · doi:10.18103/mra.v13i8.6887 · Cited by 11

Digital Twin in Health Care

Atalay, S., & SÖNMEZ, U. (2023) · Springer eBooks · doi:10.1007/978-981-99-0252-1_10 · Cited by 11

Machine learning based models for implementing digital twins in healthcare industry

Balasubramaniam, S., Sumina, S., Kumar, K. S., & Prasanth, A. (2024) · Elsevier eBooks · doi:10.1016/b978-0-443-13565-1.00009-9 · Cited by 11

Digital twins for cardiovascular diseases: towards personalised and sustainable care

Vallée, A. (2025) · Acta cardiologica. Supplementum · doi:10.1080/00015385.2025.2569027 · Cited by 11

Melanoma 2.0. Skin cancer as a paradigm for emerging diagnostic technologies, computational modelling and artificial intelligence

Vera, J., Lai, X., Baur, A. S., Erdmann, M., Gupta, S. K., Guttà, C., Heinzerling, L., Heppt, M. V., Kazmierczak, P. M., Kunz, M., et al. (2022) · Briefings in Bioinformatics · doi:10.1093/bib/bbac433 · Cited by 11

Digital Twin Technology - Fundamentals and Applications

Korhan, O. (2023) · Industrial engineering and management. · doi:10.5772/intechopen.104048 · Cited by 11

Enhancing Ophthalmic Care: The Transformative Potential of Digital Twins in Healthcare

Banoub, R. G., Sanghvi, H. A., Gill, G. S., Paredes, A. A., Bains, H. K., Patel, A., Agarwal, A., & Gupta, S. (2024) · Cureus · doi:10.7759/cureus.76209 · Cited by 10

Do urban digital twins need agents?

Russo, L. M., Dane, G. Z., Helbich, M., Ligtenberg, A., Filomena, G., Janssen, C. P., Koeva, M., Nourian, P., Patuano, A., Raposo, P., et al. (2025) · Environment and Planning B Urban Analytics and City Science · doi:10.1177/23998083251317666 · Cited by 10

Approach to implant monitoring and data processing with digital implant lifecycle management

Denkena, B., Wichmann, M., Eggers, M.-E., Emonde, C. K., & Hurschler, C. (2025) · Scientific Reports · doi:10.1038/s41598-025-99975-w · Cited by 10

Single-cell multi-omics for precision cardiovascular and longevity medicine: from methods to clinical translation

Osório, T. G., Pavesi, E., Abou‐El‐Ardat, K., Qureshi, N., Cassidy, L., John, T. L. S., Sirotin, N., & Piechowski‐Jóźwiak, B. (2025) · Frontiers in Aging · doi:10.3389/fragi.2025.1656727 · Cited by 11

Tailored Therapy Regimes Using Digital Twins

Sathish, A., Ranjan, A., & Mahek, A. (2024) · Advances in medical technologies and clinical practice book series · doi:10.4018/979-8-3693-5893-1.ch006

Digital twins are integral to personalizing medicine and improving public health

Johnson, B., & Curtius, K. (2024) · Nature Reviews Gastroenterology & Hepatology · doi:10.1038/s41575-024-00992-3 · Cited by 11

Closing the loop in personalized medicine

Hernandez-Vargas, E. A. (2022) · Elsevier eBooks · doi:10.1016/b978-0-32-390171-0.00010-x

The Digital Twin Revolution in Personalised Medicine

Mehrin, S., Rayapudi, V. S. S., Laudia, A. C., & Rao, T. R. (2025) · International Journal of Biomedical Engineering and Technology · doi:10.1504/ijbet.2025.10072020

Toward mechanistic medical digital twins: some use cases in immunology

Laubenbacher, R., Adler, F., An, G. C., Castiglione, F., Eubank, S., Fonseca, L. L., Glazier, J. A., Helikar, T., Jett‐Tilton, M., Kirschner, D. E., et al. (2024) · Frontiers in Digital Health · doi:10.3389/fdgth.2024.1349595 · Cited by 66