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

Conceptual Molecular Communication Solution for Developing Digital Twin to Enable Precision Medicine Implementation

Chude-Okonkwo, U. A. K. (2021) · International Conference on Signal Processing and Communication Systems · doi:10.1109/icspcs53099.2021.9660222 · Cited by 10

TwinSync: A Digital Twin Synchronization Protocol for Bandwidth-Limited IoT Applications

Kalasapura, D., Li, J.-Y., Liu, S.-Z., Chen, Y., Wang, R., Abdelzaher, T., Caesar, M., Bhattacharyya, J., Kim, J. H., Wang, G., et al. (2023) · International Conference on Computer Communications and Networks · doi:10.1109/icccn58024.2023.10230154 · Cited by 15

Digital Twins in Healthcare: Security, Privacy, Trust and Safety Challenges

Jørgensen, C. S., Shukla, A., & Katt, B. (2024) · Lecture notes in computer science · doi:10.1007/978-3-031-54129-2_9 · Cited by 10

Future perspectives of digital twin technology in orthodontics

Ma, Y., Li, Y., Liu, X., Gao, J., Wang, A., chen, H., Liu, Z., & Jin, Z. (2024) · Displays · doi:10.1016/j.displa.2024.102818 · Cited by 10

Digital twin of patient in clinical workflow

Wickramasinghe, N. S., Ulapane, N. N. B., Andargoli, A., Shuakat, M. N., Nguyen, T. A., Zelcer, J., & Vaughan, S. (2023) · Proceedings of the Royal Society of Victoria · doi:10.1071/rs23013 · Cited by 9

Digital Twin for Neurology: An Introduction to a New Frontier in Healthcare

Ashraf, T., Chishti, M. A., & Raheem, M. M. (2024) · Learning and Technology Conference (L&T) · doi:10.1109/lt60077.2024.10469438 · Cited by 9

Predictive Modeling of Human Skin Deformation and Growth During Tissue Expansion in Postmastectomy Breast Reconstruction

Laudo, J., Han, T., Ledwon, J. K., Figueroa, A. E., Gosain, A. K., Lee, T., & Tepole, A. B. (2025) · Journal of Biomechanical Engineering · doi:10.1115/1.4068370 · Cited by 9

Reimagining ethnopharmacology with generative AI: Towards inclusive, ethical, and data-driven traditional medicine

Bhadra, S., Pundir, C., Mukherjee, M., Kar, A., Banerjee, S., Charoensup, R., Duangyod, T., & Mukherjee, P. K. (2025) · Pharmacological Research · doi:10.1016/j.phrs.2025.108002 · Cited by 10

Cardiometabolic risk reduction with digital twinning in patients with type 2 diabetes

Seyedi, S. A., Gonzalez-Rivas, J. P., Mellacheruvu, P., Mellacheruvu, A., Aledavood, S. P., Esteghamati, A., & Mechanick, J. I. (2025) · Cardiovascular Diabetology – Endocrinology Reports · doi:10.1186/s40842-025-00242-8 · Cited by 9

From prediction to intervention: causal digital twins for personalized clinical decision support

Vallée, A. (2026) · Journal of Translational Medicine · doi:10.1186/s12967-026-07895-8 · Cited by 12

Digital twins in surgery: achievements and limitations

Kurakova, N. G., Цветкова, Л. А., & Polyakova, Y. V. (2022) · Pirogov Russian Journal of Surgery · doi:10.17116/hirurgia202205197 · Cited by 9

Perspective on investigation of neurodegenerative diseases with neurorobotics approaches

Tolu, S., Strohmer, B., & Zahra, O. (2023) · Neuromorphic Computing and Engineering · doi:10.1088/2634-4386/acc2e1 · Cited by 9

An Ecosystem of Digital Twins for Operating Room Management

Burattini, S., Montagna, S., Croatti, A., Gentili, N., Ricci, A., Leonardi, L., Pandolfini, S., & Tosi, S. (2023) · Proceedings - IEEE Symposium on Computer-Based Medical Systems · doi:10.1109/cbms58004.2023.00317 · Cited by 9

Perspective Chapter: Digital Twins for Health – Opportunities, Barriers and a Path Forward

Armeni, P., Polat, I., Rossi, L. M. D., Diaferia, L., Visioli, G., Meregalli, S., & Gatti, A. M. (2023) · Industrial engineering and management. · doi:10.5772/intechopen.112490 · Cited by 9

Digital-Twin-Assisted Academic Environment Monitoring for Anxiety Disorder

Manocha, A., Sood, S. K., & Bhatia, M. (2023) · IEEE Internet of Things Journal · doi:10.1109/jiot.2023.3337846 · Cited by 9

Large-scale knowledge graph representations of disease processes

Hoch, M., Gupta, S. K., & Wolkenhauer, O. (2024) · Current Opinion in Systems Biology · doi:10.1016/j.coisb.2024.100517 · Cited by 9

The concept of using digital twins to predict the values of leading indicators of patients' condition

Grinevich, V. B., Kryukov, E. V., Minakov, E. P., & Seliverstov, P. V. (2025) · Vrach · doi:10.29296/25877305-2025-09-16 · Cited by 9

Generating synthetic data with a mechanism-based Critical Illness Digital Twin: Demonstration for Post Traumatic Acute Respiratory Distress SyndromePreprint

Cockrell, C., Schobel, S., Lisboa, F., Yoram Vodovotz, B., & An, G. C. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.11.22.517524 · Cited by 9

Machine Learning Efforts That Enhance Personalized Patient Care and Chronic Disease Management

Adeyinka, A. A., Lamina, Y., Tawo, O. E., Adeyeye, Y. I., & Minkah, A. Y. (2022) · International Journal of Scientific Research in Science and Technology · doi:10.32628/ijsrst2302551 · Cited by 8

AI-powered programmable virtual humans toward human physiologically-based drug discovery

Wu, Y., Bourne, P. E., & Xie, L. (2025) · Drug Discovery Today · doi:10.1016/j.drudis.2025.104497 · Cited by 8

MS360°: a conceptual digital-first, data-driven hybrid care framework for personalised multiple sclerosis management

Voigt, I., Masanneck, L., Pawlitzki, M., Inojosa, H., Meuth, S. G., & Ziemssen, T. (2026) · npj Digital Medicine · doi:10.1038/s41746-026-02461-4 · Cited by 8

A probabilistic neural twin for treatment planning in peripheral pulmonary artery stenosis

Lee, J. D., Richter, J., Pfaller, M. R., Szafron, J. M., Menon, K., Zanoni, A., Ma, M., Feinstein, J. A., Kreutzer, J. N., Marsden, A. L., et al. (2024) · International Journal for Numerical Methods in Biomedical Engineering · doi:10.1002/cnm.3820 · Cited by 8

Disease progression modeling with temporal realignment: An emerging approach to deepen knowledge on chronic diseases

Yoshioka, H., Jin, R., Hisaka, A., & Suzuki, H. (2024) · Pharmacology & Therapeutics · doi:10.1016/j.pharmthera.2024.108655 · Cited by 9

Configuration Testing of an Artificial Pancreas System Using a Digital Twin: An Evaluative Case Study

Somers, R. J., Walkinshaw, N., Hierons, R. M., Elliott, D., Iqbal, A., & Walkinshaw, E. (2025) · Software Testing Verification and Reliability · doi:10.1002/stvr.70000 · Cited by 8

A Solution for the Health Data Sharing Dilemma: Data-Less and Identity-Less Model Sharing Through Federated Learning and Digital Twin-Assisted Clinical Decision Making

Wickramasinghe, N. S., & Ulapane, N. N. B. (2025) · Electronics · doi:10.3390/electronics14040682 · Cited by 8

TWINVAX: conceptual model of a digital twin for immunisation services in primary health care

El-Warrak, L. D. O., & de Farias, C. M. (2025) · Frontiers in Public Health · doi:10.3389/fpubh.2025.1568123 · Cited by 7

Simulation-based assessment of digital twin systems for immunisation

El-Warrak, L. D. O., de Farias, C. M., & Costa, V. H. D. M. D. A. (2025) · Frontiers in Digital Health · doi:10.3389/fdgth.2025.1603550 · Cited by 7

Digital twins assisted surgery: A conceptual framework for transforming surgical training and navigation

Kyeremeh, J., Asciak, L., Blackmur, J. P., Luo, X., Picard, F., Shu, W., & Stewart, G. D. (2025) · The Surgeon · doi:10.1016/j.surge.2025.09.007 · Cited by 7

G protein-coupled receptor digital twins for precision and personalized medicine

Boeringer, T., Pardo, M., Craig, C. J., & Maudsley, S. R. (2025) · Computational and Structural Biotechnology Journal · doi:10.1016/j.csbj.2025.11.042 · Cited by 8

Digital Twins for Just-in-Time Adaptive Interventions (JITAIs): Framework for Optimizing and Continually Improving JITAIs

Gazi, A. H., Gao, D., Ghosh, S., Xu, Z., Trella, A. L., Klasnja, P., & Murphy, S. A. (2025) · Journal of Medical Internet Research · doi:10.2196/72830 · Cited by 8

Traditional Chinese Medicine Modernization in Diagnosis and Treatment: Utilizing Artificial Intelligence and Nanotechnology

Yu, W., Chen, M., Tan, X., Wei, X., Sun, F., Yan, H., Xu, X. J., & Shang, H. (2026) · MedComm · doi:10.1002/mco2.70596 · Cited by 8

Multiscale predictive cellular modeling: integrating hypothesis grammars, digital twins, and multi-omics for In silico oncology and precision theranostics

Gopukumar, S. T., Dwivedi, D., Rahamathulla, M., Ahmed, M. M., Soni, T. K., Natarajan, P. G., Ramkanth, S., Mitra, A., & Das, U. (2026) · Functional & Integrative Genomics · doi:10.1007/s10142-026-01890-4 · Cited by 7

Calibration of the Double Digital Twin for the Hand Rehabilitation by the Virtual Glove

Matteo, A. D., Lozzi, D., Mattei, E., Mignosi, F., Montagna, S., Polsinelli, M., & Placidi, G. (2024) · Proceedings - IEEE Symposium on Computer-Based Medical Systems · doi:10.1109/cbms61543.2024.00092 · Cited by 7

Virtual medical astronaut avatars for future deep space missions

Urlings, C., Baselet, B., Tabury, K., & Baatout, S. (2024) · Frontiers in Space Technologies · doi:10.3389/frspt.2024.1423138 · Cited by 7

Modulation of the cytoskeleton for cancer therapy

Matov, A. (2026) · Frontiers in Cell and Developmental Biology · doi:10.3389/fcell.2025.1681065 · Cited by 7

A Plea for (In)Human-centred AI

Braun, M., & Meacham, D. (2024) · Philosophy & Technology · doi:10.1007/s13347-024-00785-1 · Cited by 6

Precision, Prediction and Progress: A New Era in Pharmacology

Singh, J. P., Gaur, V., & Dubey, P. (2025) · doi:10.38124/ijisrt/25apr1322 · Cited by 6

Impact of Digital Twins on Real Practices in Manufacturing Industries

Khan, M. Q., Alvi, M. A. H., Nawaz, H., & Umar, M. (2025) · Inventions · doi:10.3390/inventions10060106 · Cited by 6

Current Status on the Convergence of Artificial Intelligence and Formulation Development in Industry: A Review

Warke, S., Katari, O., & Jain, S. (2025) · AAPS PharmSciTech · doi:10.1208/s12249-025-03296-0 · Cited by 8

Digital Twins and Health Care: an Umbrella Review

Afshar, M., Moradkhani, A., Soheili, M., Tavakkol, M., Moradi, Y., & Kohan, H. G. (2025) · Journal of Medical Systems · doi:10.1007/s10916-025-02322-9 · Cited by 6

Digital twins in healthcare administration: A systematic review on novel approaches to management and planning

Гаранин, А. А., Aidumova, O. Y., & Kiselev, A. R. (2025) · Russian Open Medical Journal · doi:10.15275/rusomj.2025.0104 · Cited by 6

On the scaling of digital twins by aggregation

Pias, M. R., Bull, L. A., Brennan, D. S., Girolami, M., & Crowcroft, J. (2025) · Data & Policy · doi:10.1017/dap.2024.86 · Cited by 6

Limiting medical certainties? Funding challenges for German and comparable public healthcare systems due to AI prediction and how to address them

von Ulmenstein, U. F., Tretter, M., Ehrlich, D. B., & von Peharnik, C. L. (2022) · Frontiers in Artificial Intelligence · doi:10.3389/frai.2022.913093 · Cited by 8

A multimodal analysis of genomic and RNA splicing features in myeloid malignancies

Durmaz, A., Gurnari, C., Hershberger, C. E., Pagliuca, S., Daniels, N. J., Awada, H. K., Awada, H., Ademà, V., Mori, M., Ponvilawan, B., et al. (2023) · iScience · doi:10.1016/j.isci.2023.106238 · Cited by 6

Digital twin manifesto for the pathology laboratory

Eccher, A., Pagni, F., Dominici, M., Bonetti, L. R., Marletta, S., Munari, E., Cazzaniga, G., Parwani, A. V., L’Imperio, V., & Tos, A. P. D. (2025) · Diagnostic Pathology · doi:10.1186/s13000-025-01679-2 · Cited by 5

A semi-mechanistic mathematical framework for simulating multi-hormone dynamics in reproductive endocrinology

Vallée, A., Féki, A., Moawad, G., & Ayoubi, J.-M. (2025) · Computational and Structural Biotechnology Journal · doi:10.1016/j.csbj.2025.08.013 · Cited by 5

The New Era of Holistic and Precision Dentistry with Integration of Digital Twin Technology: A Scoping Review

Thribhuvanan, L., Saravanakumar, M., Panikkar, P., & Durairaj, P. (2025) · International Journal of Clinical Pediatric Dentistry · doi:10.5005/jp-journals-10005-3234 · Cited by 5

Lost in translation: why digital twins thrive in research but falter in politics and public administration

Richter, F., Campbell, K., & Riedl, J. (2025) · Data & Policy · doi:10.1017/dap.2025.10027 · Cited by 6

Digital twins technology in endodontics: from reactive to predictive – a new frontier towards personalised root canal treatment

Turky, M., & Dummer, P. M. H. (2026) · BDJ · doi:10.1038/s41415-025-9456-y · Cited by 5

Bridging evidence worlds: policy and practice pathways for integrating clinical trials and real-world data in drug development and HTA

Sagkriotis, A. (2026) · Frontiers in Pharmacology · doi:10.3389/fphar.2026.1786017 · Cited by 5

Multifactorial pathogenesis of rheumatoid arthritis: interaction between inflammation, metabolic dysregulation, and tissue mechanics

Xu, Y., Yang, Q., Lu, H., Zhang, J., Xu, J., Liu, X., Wang, J., Xie, Z., & Li, Z. (2026) · Frontiers in Immunology · doi:10.3389/fimmu.2026.1825523 · Cited by 6

Kişiselleştirilmiş Tıp İçin Dijital İkiz: Sistematik Derleme

Dilek, A. L. A. Y. (2024) · Sağlık Profesyonelleri Araştırma Dergisi · doi:10.57224/jhpr.1342561 · Cited by 5

Towards Digital Twins in Healthcare: Optimizing Operating Room and Recovery Room Dynamics

Pellegrino, M., Lombardo, G., & Poggi, A. (2024) · Procedia Computer Science · doi:10.1016/j.procs.2024.09.338 · Cited by 5

Advancing digital health in information systems research: Insights from a text mining analysis

Weissenfels, S., Nissen, A., & Smolnik, S. (2025) · Electronic Markets · doi:10.1007/s12525-025-00768-w · Cited by 5

The Advent of the Digital Twin: A Prospective in Healthcare in the Next Decade

Rojas-Arce, J. L., & Ortega-Maldonado, E. C. (2021) · IFIP advances in information and communication technology · doi:10.1007/978-3-030-85910-7_26 · Cited by 5

‘We cannot paint them all with the same brush’: the need for a better definition of patients with myelodysplastic syndromes for clinical trial design

Gurnari, C., & Visconte, V. (2021) · British Journal of Haematology · doi:10.1111/bjh.17909 · Cited by 5

Creating Simulated Equivalents to Project Long-Term Population Health Outcomes of Underserved Patients: An Application to Colorectal Cancer Screening

Koutouan, P. R., Mayorga, M. E., O’Leary, M. C., & Lich, K. H. (2021) · Winter Simulation Conference · doi:10.1109/wsc52266.2021.9715374 · Cited by 5

Principles of Precision Medicine

Larijani, B. A., Meybodi, H. R. A., Sarhangi, N., & Hasanzad, M. (2022) · Springer eBooks · doi:10.1007/978-981-19-5082-7_1 · Cited by 5

A Systematic Review: Digital Twin in Healthcare

S, R. M. (2023) · International Journal for Research in Applied Science and Engineering Technology · doi:10.22214/ijraset.2023.52792 · Cited by 5

Role of Intelligent Virtual Agents in Medical and Health Domains

Ivanović, M. D., Bădică, C., & Bădică, A. (2022) · International Conference on Innovations in Intelligent Systems and Applications (INISTA) · doi:10.1109/inista55318.2022.9894253 · Cited by 5

Artificial intelligence in modern medicine- evolving necessity of the present and role in transforming the future of medical care (Preprint)Preprint

Bhattad, P. B., & Jain, V. K. (2020) · doi:10.2196/preprints.18829 · Cited by 5

EndoFinder: Online Image Retrieval for Explainable Colorectal Polyp Diagnosis

Yang, R., Zhu, Y., Fu, P., Zhang, Y., Wang, Z., Li, Q., Zhou, P., Yang, X., & Wang, S. (2024) · Lecture notes in computer science · doi:10.1007/978-3-031-72117-5_24 · Cited by 4

Digital Twin Types and Applications in Healthcare

Pop, E., Iliuţă, M.-E., & Moisescu, M. A. (2024) · Studies in health technology and informatics · doi:10.3233/shti241056 · Cited by 4

Mainstream Artificial Intelligence Technologies in Contemporary Ophthalmology

Yin, S., Wang, L., Wu, S., Jiang, J., Qiang, W., Wang, Y., Wang, S., Shao, Y., Chen, W., & Li, Z. (2025) · Advanced Intelligent Systems · doi:10.1002/aisy.202500055 · Cited by 5

A roadmap for AI-aided digital twins in computational nuclear oncology: A position paper by the EANM

Cavinato, L., Kirienko, M., Papp, L., Shi, K., Visvikis, D., Chiti, A., & Sollini, M. (2025) · The EANM Journal · doi:10.1016/j.eanmj.2025.100007 · Cited by 4

Internet of Medical Things: Architecture, Trends, Challenges, and the Evolution Towards IoMT 5.0

Kadam, D., Budaragade, A. P., Salunkhe, U. N., Gurav, U., & Patil, A. (2025) · Computer Networks and Communications · doi:10.37256/cnc.3220257676 · Cited by 4

Single‐cell digital twins identify drug targets and repurposable medicine in Alzheimer’s disease

Ren, Y., Hu, M., Li, Y. E., Pieper, A. A., Cummings, J. L., & Cheng, F. (2025) · Alzheimer s & Dementia · doi:10.1002/alz70859_102982 · Cited by 4

A study of the transformation of digital twins into personalized medicine

Seliverstov, P. V., Владимирович, К. Е., Grinevich, V. B., Ivchenko, E. V., & Minakov, E. (2025) · Molekulyarnaya Meditsina (Molecular medicine) · doi:10.29296/24999490-2025-06-11 · Cited by 4

Knowledge graphs in food and nutrition: Applications, challenges, and future directions

Lv, C., QiongE, D., Zhu, F., Li, Z., Xiao, R., Zhang, Z., Gao, Y., Fang, Y., Sun, C., Gan, D., et al. (2026) · Trends in Food Science & Technology · doi:10.1016/j.tifs.2026.105830 · Cited by 4

Human digital twins in personalized and predictive healthcare: a comprehensive review of technologies, applications, and future directions

Babu, A. M., & Madhan, E. S. (2026) · Frontiers in Digital Health · doi:10.3389/fdgth.2026.1827007 · Cited by 4

A Proposed Framework for Digital Twins Driven Precision Medicine Platform: Values and Challenges

Elshaier, Y. A. M. M., Hassanien, A. E., Darwsih, A., & Al-Qaheri, H. (2022) · Studies in systems, decision and control · doi:10.1007/978-3-030-96802-1_4 · Cited by 4

The Role of Digital Twins in Personalized Sleep Medicine

Alarcón, Á. S., Madrid, N. M., Seepold, R., & Ortega, J. A. (2022) · Lecture notes in bioengineering · doi:10.1007/978-3-031-16855-0_8 · Cited by 4

Hyperreal Patients. Digital Twins as Simulacra and their impact on clinical heuristics

Rubeis, G. (2023) · Techno:Phil · doi:10.1007/978-3-662-65868-0_10 · Cited by 4

A Digital Twins Approach for Oncologic Pharmaceutical Supply Chain

Burattini, S., Montagna, S., Gentili, N., Galardi, F., Vespignani, R., Zanatto, P., Croatti, A., & Ricci, A. (2024) · IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops) · doi:10.1109/percomworkshops59983.2024.10502569 · Cited by 4

Expert Perspectives on Future 6G-Enabled Hospital Metaverse

Wang, F. F., Jurva, R., Ahokangas, P., Yrjölä, S., & Matinmikko‐Blue, M. (2024) · Communications in computer and information science · doi:10.1007/978-3-031-59080-1_1 · Cited by 4

Optimizing Batch Crystallization with Model-based Design of Experiments

Lynch, H. G., Bjarnason, A., Laky, D. J., Brown, C. J., & Dowling, A. W. (2024) · Systems and Control Transactions · doi:10.69997/sct.152239 · Cited by 4

Building virtual patients using simulation-based inference

Paul, N., Karamitsou, V., Giegerich, C., Sadeghi, A., Lücke, M., Wagenhuber, B., Kister, A., & Rehberg, M. (2024) · Frontiers in Systems Biology · doi:10.3389/fsysb.2024.1444912 · Cited by 4

Digital Twins in Drug Discovery: A Paradigm Shift Shaping Pharmaceutical Innovation

Iswariya, V. T., Asireddy, S. R., Vallarapu, N. K., Madhira, J., & Rao, T. R. (2024) · International Journal of Pharmaceutical Sciences and Nanotechnology · doi:10.37285/ijpsn.2024.17.5.9 · Cited by 4

PROTOTWIN-PET: A Deep Learning and GPU-Based Workflow for Dose Verification in Proton Therapy With PET

Cabrales, P., Onecha, V. V., Izquierdo‐Garcia, D., Fraile, L. M., Udías, J. M., & Herraiz, J. L. (2025) · IEEE Transactions on Radiation and Plasma Medical Sciences · doi:10.1109/trpms.2025.3531536 · Cited by 4

MODalyseR—a novel software for inference of disease module hub regulators identified a putative multiple sclerosis regulator supported by independent eQTL data

de Weerd, H. A., Åkesson, J., Guala, D., Gustafsson, M., & Lubovac-Pilav, Z. (2022) · Bioinformatics Advances · doi:10.1093/bioadv/vbac006 · Cited by 4

Robust parallel nonlinear solvers for implicit time discretizations of the Bidomain equations with staggered ionic models

Barnafi, N. A., Huynh, N. M. M., Pavarino, L. F., & Scacchi, S. (2024) · Computers & Mathematics with Applications · doi:10.1016/j.camwa.2024.04.014 · Cited by 4

Digitalisierung in der onkologischen Chirurgie

Wilhelm, D., Berlet, M., Feußner, H., & Ostler, D. (2020) · Forum · doi:10.1007/s12312-020-00879-9 · Cited by 4

Machine Learning–Enabled Digital Twins for Diagnostic and Therapeutic Purposes

Shah, N., Nagar, J., Desai, K., Bhatt, N., Bhatt, N., & Mewada, H. K. (2024) · Wiley eBooks · doi:10.1002/9781394287420.ch5 · Cited by 4

Data-Driven Defragmentation: Achieving Value-Based Sarcoma and Rare Cancer Care Through Integrated Care Pathway Mapping

Fuchs, B., & Heesen, P. (2025) · Journal of Personalized Medicine · doi:10.3390/jpm15050203 · Cited by 3

Digital twins in urology: a vision for the future of urological practice

Nedbal, C., Madaan, S., Ghulam, N., & Somani, B. K. (2026) · Therapeutic Advances in Urology · doi:10.1177/17562872261419592 · Cited by 3

Medical Digital Twin Technology for Interoperability: Challenges and Opportunities

Alang, T. A. I. T., Lee, Y. Y., Tan, T. X., & Mokhtar, A. M. (2026) · Biomedical Engineering and Computational Biology · doi:10.1177/11795972261431928 · Cited by 3

Mapping the landscape of AI-driven digital twins in medical diagnosis: A scoping review on core technologies, applications, and implementation barriers

Shen, S., Qi, W., Liu, X., Zeng, J., Li, S., Peng, G., Li, P., Wang, J., Lü, X., & Cao, S. (2026) · Artificial Intelligence in Medicine · doi:10.1016/j.artmed.2026.103474 · Cited by 3

Fifteen challenges for generative AI applications to cell biology

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