{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,29]],"date-time":"2026-05-29T20:51:50Z","timestamp":1780087910710,"version":"3.54.0"},"reference-count":54,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2026,3,17]],"date-time":"2026-03-17T00:00:00Z","timestamp":1773705600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100006602","name":"Air Force Research Laboratory","doi-asserted-by":"crossref","award":["BAA-FA8650-18-S-1201"],"award-info":[{"award-number":["BAA-FA8650-18-S-1201"]}],"id":[{"id":"10.13039\/100006602","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/100009226","name":"National Security Agency","doi-asserted-by":"crossref","award":["4B991"],"award-info":[{"award-number":["4B991"]}],"id":[{"id":"10.13039\/100009226","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/100009226","name":"National Security Agency","doi-asserted-by":"crossref","award":["047814256"],"award-info":[{"award-number":["047814256"]}],"id":[{"id":"10.13039\/100009226","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Information"],"abstract":"<jats:p>Bilateral idiopathic carpal tunnel syndrome (CTS) is a neuromuscular condition involving the compression of the median nerve at both wrists, leading to pain, neurological symptoms, and loss of function. This paper proposes a robust machine-learning framework for a randomized crossover clinical trial comparing two physiotherapeutic treatment regimens: stretching followed by myofascial mobilization (S\/M) and the reverse sequence (M\/S). Instead of making inferences about the superiority of one treatment over another, the treatment regimen serves as a structured analytical label for investigating predictive separability, feature representation, and model stability within a controlled experimental setting. The clinical dataset of 73 patients underwent rigorous preprocessing, including strength feature aggregation and principal component analysis (PCA). Various classifiers were evaluated, with CatBoost achieving an ROC-AUC of 0.985 and a test accuracy of 96.5%, while Random Forest demonstrated strong adversarial robustness with an adversarial accuracy of 96.83%. To assess robustness, clinically constrained perturbations were introduced into the PCA feature space, simulating realistic input variability. The findings indicate that ensemble learning algorithms can capture structured patterns in crossover clinical datasets and remain stable under low-magnitude adversarial perturbations. The study underscores the importance of robustness evaluation and interpretability when applying machine learning models to biomedical data, particularly in small and well-structured clinical cohorts.<\/jats:p>","DOI":"10.3390\/info17030293","type":"journal-article","created":{"date-parts":[[2026,3,17]],"date-time":"2026-03-17T14:03:27Z","timestamp":1773756207000},"page":"293","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["A Secure and Robust ML Framework for Sequence Classification and Adversarial Evaluation in a Bilateral Carpal Tunnel Syndrome Crossover Dataset"],"prefix":"10.3390","volume":"17","author":[{"ORCID":"https:\/\/orcid.org\/0009-0009-0250-410X","authenticated-orcid":false,"given":"Pratik Pandurang","family":"Kharat","sequence":"first","affiliation":[{"name":"Department of Computer Science and Engineering, Wright State University, Dayton, OH 45435, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9077-2156","authenticated-orcid":false,"given":"Sufian","family":"Al Majmaie","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, Wright State University, Dayton, OH 45435, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-8370-9417","authenticated-orcid":false,"given":"Ghazal","family":"Ghajari","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, Wright State University, Dayton, OH 45435, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7582-8326","authenticated-orcid":false,"given":"Fathi","family":"Amsaad","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, Wright State University, Dayton, OH 45435, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8000-4161","authenticated-orcid":false,"given":"Mohamed I.","family":"Ibrahem","sequence":"additional","affiliation":[{"name":"Cyber Systems Engineering Department, Augusta University, Augusta, GA 30912, USA"},{"name":"Department of Electrical Engineering, Faculty of Engineering at Shoubra, Benha University, Cairo 11672, Egypt"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,3,17]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"153","DOI":"10.1001\/jama.282.2.153","article-title":"Prevalence of carpal tunnel syndrome in a general population","volume":"282","author":"Atroshi","year":"1999","journal-title":"JAMA"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"CPG1","DOI":"10.2519\/jospt.2019.0301","article-title":"Hand pain and sensory deficits: Carpal tunnel syndrome: Clinical practice guidelines linked to the international classification of functioning, disability and health from the academy of hand and upper extremity physical therapy and the academy of orthopaedic physical therapy of the American physical therapy association","volume":"49","author":"Erickson","year":"2019","journal-title":"J. Orthop. Sport. Phys. Ther."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"79","DOI":"10.1016\/j.pjnns.2017.09.009","article-title":"Bilateral carpal tunnel syndrome\u2014A review","volume":"52","author":"Dec","year":"2018","journal-title":"Neurol. I Neurochir. Pol."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"110838","DOI":"10.1016\/j.dib.2024.110838","article-title":"Dataset on bilateral idiopathic carpal tunnel syndrome: Crossover study of two combined physiotherapeutic treatment methods on chirurgical and clinical patients","volume":"56","author":"Georgeto","year":"2024","journal-title":"Data Brief"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"1297","DOI":"10.1136\/bmj.280.6227.1297","article-title":"Idiopathic carpal tunnel syndrome caused by carpal stenosis","volume":"280","author":"Dekel","year":"1980","journal-title":"Br. Med. J."},{"key":"ref_6","first-page":"CD003219","article-title":"Non-surgical treatment (other than steroid injection) for carpal tunnel syndrome","volume":"2003","author":"Marshall","year":"2003","journal-title":"Cochrane Database Syst. Rev."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"246","DOI":"10.1016\/j.jbmt.2008.03.007","article-title":"The effect of mechanical load on degenerated soft tissue","volume":"12","author":"Hammer","year":"2008","journal-title":"J. Bodyw. Mov. Ther."},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"AbdelRaouf, H., Hasnaine, Q.R., Fouda, M.M., Fadlullah, Z.M., and Ibrahem, M.I. (2026). Paradigm Shift Toward Distributed Learning in IoT Intelligence: A Comprehensive Survey of Opportunities and Challenges. IEEE Internet Things J., 1.","DOI":"10.1109\/JIOT.2026.3657733"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"2505","DOI":"10.1109\/COMST.2024.3486690","article-title":"Privacy-Preserving Data-Driven Learning Models for Emerging Communication Networks: A Comprehensive Survey","volume":"27","author":"Fouda","year":"2025","journal-title":"IEEE Commun. Surv. Tutor."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"47223","DOI":"10.1109\/JIOT.2025.3602942","article-title":"Empowering AI-Driven Healthcare With Secure, Decentralized, and Privacy-Enhancing Adaptive Intelligence","volume":"12","author":"AbdelRaouf","year":"2025","journal-title":"IEEE Internet Things J."},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"AbdelRaouf, H., Abouyoussef, M., Fouda, M.M., Md Fadlullah, Z., and Ibrahem, M.I. (2025). Towards Decentralized, Secure, and Efficient Adaptive Learning for Robust Healthcare Monitoring. Proceedings of the ICC 2025\u2014IEEE International Conference on Communications, Montreal, QC, Canada, 8\u201312 June 2025, IEEE.","DOI":"10.1109\/ICC52391.2025.11161996"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"24","DOI":"10.1038\/s41591-018-0316-z","article-title":"A guide to deep learning in healthcare","volume":"25","author":"Esteva","year":"2019","journal-title":"Nat. Med."},{"key":"ref_13","unstructured":"Paget, J. (1853). Lectures on Surgical Pathology, Longman."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"69","DOI":"10.2174\/1874325001206010069","article-title":"Carpal tunnel syndrome: A review of the recent literature","volume":"6","author":"Ibrahim","year":"2012","journal-title":"Open Orthop. J."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"243","DOI":"10.1007\/s10072-009-0213-9","article-title":"Diagnosis, treatment and follow-up of the carpal tunnel syndrome: A review","volume":"31","author":"Alfonso","year":"2010","journal-title":"Neurol. Sci."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Abdelraouf, M.M., Ahmed, A.I., and Elghitany, N.A. (2021). Sono-Elastography in evaluation of the median nerve in carpal tunnel syndrome patients. QJM Int. J. Med., 114.","DOI":"10.1093\/qjmed\/hcab106.052"},{"key":"ref_17","first-page":"e7333","article-title":"Carpal tunnel syndrome: A review of literature","volume":"12","author":"Genova","year":"2020","journal-title":"Cureus"},{"key":"ref_18","first-page":"e27053","article-title":"Carpal tunnel syndrome: Pathophysiology and comprehensive guidelines for clinical evaluation and treatment","volume":"14","author":"Joshi","year":"2022","journal-title":"Cureus"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"805","DOI":"10.1007\/s00264-024-06395-y","article-title":"Carpal tunnel syndrome diagnosis as a risk factor for falls","volume":"49","author":"Lakhlani","year":"2025","journal-title":"Int. Orthop."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"1102","DOI":"10.1093\/oxfordjournals.aje.a115753","article-title":"Risk factors for carpal tunnel syndrome","volume":"132","author":"Kester","year":"1990","journal-title":"Am. J. Epidemiol."},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Lakshminarayanan, K., Shah, R., and Li, Z.M. (2019). Sex-related differences in carpal arch morphology. PLoS ONE, 14.","DOI":"10.1371\/journal.pone.0217425"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"1654","DOI":"10.1111\/os.13705","article-title":"Bilateral Idiopathic Carpal Tunnel Syndrome: Clinical-Functional Characterization and Efficacy of Two Combined Postoperative Physiotherapeutic Treatments","volume":"15","author":"Georgeto","year":"2023","journal-title":"Orthop. Surg."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"2153","DOI":"10.1016\/S0140-6736(25)00368-X","article-title":"Surgery versus corticosteroid injection for carpal tunnel syndrome (DISTRICTS): An open-label, multicentre, randomised controlled trial","volume":"405","author":"Palmbergen","year":"2025","journal-title":"Lancet"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"3250","DOI":"10.1016\/j.bjps.2022.06.070","article-title":"Outcomes of bilateral carpal tunnel syndrome treatment\u2013a systematic review and meta-analysis","volume":"75","author":"Georgeto","year":"2022","journal-title":"J. Plast. Reconstr. Aesthet. Surg."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"16757","DOI":"10.1038\/s41598-024-65840-5","article-title":"Automated segmentation of the median nerve in patients with carpal tunnel syndrome","volume":"14","author":"Moser","year":"2024","journal-title":"Sci. Rep."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"560","DOI":"10.1016\/j.jmpt.2004.10.006","article-title":"Incorporating nerve-gliding techniques in the conservative treatment of cubital tunnel syndrome","volume":"27","author":"Coppieters","year":"2004","journal-title":"J. Manip. Physiol. Ther."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"972","DOI":"10.1002\/jor.20310","article-title":"Longitudinal excursion and strain in the median nerve during novel nerve gliding exercises for carpal tunnel syndrome","volume":"25","author":"Coppieters","year":"2007","journal-title":"J. Orthop. Res."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"463","DOI":"10.1016\/j.math.2009.03.008","article-title":"The effectiveness of manual therapy in the management of musculoskeletal disorders of the shoulder: A systematic review","volume":"14","author":"Ho","year":"2009","journal-title":"Man. Ther."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"51","DOI":"10.1038\/s41746-020-0249-z","article-title":"Personalized predictions of patient outcomes during and after hospitalization using artificial intelligence","volume":"3","author":"Hilton","year":"2020","journal-title":"NPJ Digit. Med."},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Quattrocelli, S., Russo, E.F., Gatta, M.T., Filoni, S., Pellegrino, R., Cangelmi, L., Cardone, D., Merla, A., and Perpetuini, D. (2024). Integrating Machine Learning with Robotic Rehabilitation May Support Prediction of Recovery of the Upper Limb Motor Function in Stroke Survivors. Brain Sci., 14.","DOI":"10.3390\/brainsci14080759"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"02025","DOI":"10.1051\/itmconf\/20257002025","article-title":"Enhancing Rehabilitation Assessment with Artificial Intelligence: A Comprehensive Investigation of Posture Quality Prediction Using Machine Learning","volume":"70","author":"Zhang","year":"2025","journal-title":"ITM Web Conf."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"108395","DOI":"10.1016\/j.clineuro.2024.108395","article-title":"Predictors of pain intensity in carpal tunnel syndrome: Development and validation of a model","volume":"243","author":"Rezaee","year":"2024","journal-title":"Clin. Neurol. Neurosurg."},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Franco-Moreno, A., Madro\u00f1al-Cerezo, E., de Ancos-Aracil, C.L., Farf\u00e1n-Sedano, A.I., Mu\u00f1oz-Rivas, N., Bascu\u00f1ana Morej\u00f3n-Gir\u00f3n, J., Ruiz-Giard\u00edn, J.M., \u00c1lvarez-Rodr\u00edguez, F., Prada-Alonso, J., and Gala-Garc\u00eda, Y. (2024). Development of a Predictive Model of Occult Cancer After a Venous Thromboembolism Event Using Machine Learning: The CLOVER Study. Medicina, 61.","DOI":"10.3390\/medicina61010018"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"86","DOI":"10.1111\/cts.12884","article-title":"Precision medicine, AI, and the future of personalized health care","volume":"14","author":"Johnson","year":"2021","journal-title":"Clin. Transl. Sci."},{"key":"ref_35","first-page":"59","article-title":"Data-driven decision-making in healthcare: Improving patient outcomes through predictive modeling","volume":"5","author":"Adeniran","year":"2024","journal-title":"Int. J. Sch. Res. Multidiscip. Stud."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"4705","DOI":"10.1016\/j.acra.2025.02.043","article-title":"Multimodal deep learning for grading carpal tunnel syndrome: A multicenter study in China","volume":"32","author":"Shi","year":"2025","journal-title":"Acad. Radiol."},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"Tsamis, K.I., Kontogiannis, P., Gourgiotis, I., Ntabos, S., Sarmas, I., and Manis, G. (2021). Automatic electrodiagnosis of carpal tunnel syndrome using machine learning. Bioengineering, 8.","DOI":"10.3390\/bioengineering8110181"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"106","DOI":"10.1227\/NEU.0000000000001749","article-title":"Predicting clinically relevant patient-reported symptom improvement after carpal tunnel release: A machine learning approach","volume":"90","author":"Hoogendam","year":"2022","journal-title":"Neurosurgery"},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"17464","DOI":"10.1038\/s41598-021-97043-7","article-title":"Machine learning-based approach for disease severity classification of carpal tunnel syndrome","volume":"11","author":"Park","year":"2021","journal-title":"Sci. Rep."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"e4279","DOI":"10.1097\/GOX.0000000000004279","article-title":"Developing machine learning algorithms to support patient-centered, value-based carpal tunnel decompression surgery","volume":"10","author":"Harrison","year":"2022","journal-title":"Plast. Reconstr. Surg. Glob. Open"},{"key":"ref_41","doi-asserted-by":"crossref","unstructured":"Elseddik, M., Mostafa, R.R., Elashry, A., El-Rashidy, N., El-Sappagh, S., Elgamal, S., Aboelfetouh, A., and El-Bakry, H. (2023). Predicting CTS diagnosis and prognosis based on machine learning techniques. Diagnostics, 13.","DOI":"10.3390\/diagnostics13030492"},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Elseddik, M., Alnowaiser, K., Mostafa, R.R., Elashry, A., El-Rashidy, N., Elgamal, S., Aboelfetouh, A., and El-Bakry, H. (2023). Deep learning-based approaches for enhanced diagnosis and comprehensive understanding of carpal tunnel syndrome. Diagnostics, 13.","DOI":"10.3390\/diagnostics13203211"},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"111085","DOI":"10.1016\/j.ejrad.2023.111085","article-title":"Adversarial attacks in radiology\u2014A systematic review","volume":"167","author":"Sorin","year":"2023","journal-title":"Eur. J. Radiol."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"1287","DOI":"10.1126\/science.aaw4399","article-title":"Adversarial attacks on medical machine learning","volume":"363","author":"Finlayson","year":"2019","journal-title":"Science"},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"116815","DOI":"10.1016\/j.eswa.2022.116815","article-title":"Adversarial attacks and defenses on AI in medical imaging informatics: A survey","volume":"198","author":"Kaviani","year":"2022","journal-title":"Expert Syst. Appl."},{"key":"ref_46","doi-asserted-by":"crossref","unstructured":"Tsai, M.J., Lin, P.Y., and Lee, M.E. (2023). Adversarial Attacks on Medical Image Classification. Cancers, 15.","DOI":"10.3390\/cancers15174228"},{"key":"ref_47","doi-asserted-by":"crossref","unstructured":"Bhatta, N.P., Al Majmaie, S., and Amsaad, F. (2024). Feature Analysis and Model Evaluation for Classification of Hardware Trojans. Proceedings of the 2024 IEEE Physical Assurance and Inspection of Electronics (PAINE), Huntsville, AL, USA, 12\u201314 November 2024, IEEE.","DOI":"10.1109\/PAINE62042.2024.10792769"},{"key":"ref_48","unstructured":"Jolliffe, I.T. (2002). Principal Component Analysis, Springer."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"433","DOI":"10.1002\/wics.101","article-title":"Principal component analysis","volume":"2","author":"Abdi","year":"2010","journal-title":"Wiley Interdiscip. Rev. Comput. Stat."},{"key":"ref_50","first-page":"281","article-title":"Random search for hyper-parameter optimization","volume":"13","author":"Bergstra","year":"2012","journal-title":"J. Mach. Learn. Res."},{"key":"ref_51","first-page":"2825","article-title":"Scikit-learn: Machine learning in Python","volume":"12","author":"Pedregosa","year":"2011","journal-title":"J. Mach. Learn. Res."},{"key":"ref_52","first-page":"1137","article-title":"A study of cross-validation and bootstrap for accuracy estimation and model selection","volume":"Volume 2","author":"Kohavi","year":"1995","journal-title":"Proceedings of the 14th International Joint Conference on Artificial Intelligence (IJCAI), Montreal, QC, Canada, 20\u201325 August 1995"},{"key":"ref_53","unstructured":"Molnar, C. (2020). Interpretable Machine Learning: A Guide for Making Black Box Models Explainable, Lean Publishing."},{"key":"ref_54","unstructured":"Lundberg, S.M., and Lee, S.I. (2017). A Unified Approach to Interpreting Model Predictions. Proceedings of the Advances in Neural Information Processing Systems, Long Beach, CA, USA, 4\u20139 December 2017, Curran Associates Inc."}],"container-title":["Information"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2078-2489\/17\/3\/293\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,3,19]],"date-time":"2026-03-19T05:30:01Z","timestamp":1773898201000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2078-2489\/17\/3\/293"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,3,17]]},"references-count":54,"journal-issue":{"issue":"3","published-online":{"date-parts":[[2026,3]]}},"alternative-id":["info17030293"],"URL":"https:\/\/doi.org\/10.3390\/info17030293","relation":{},"ISSN":["2078-2489"],"issn-type":[{"value":"2078-2489","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,3,17]]}}}