{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,11]],"date-time":"2025-12-11T03:26:42Z","timestamp":1765423602666,"version":"3.40.4"},"reference-count":55,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2025,4,26]],"date-time":"2025-04-26T00:00:00Z","timestamp":1745625600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"},{"start":{"date-parts":[[2025,4,26]],"date-time":"2025-04-26T00:00:00Z","timestamp":1745625600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["npj Digit. Med."],"DOI":"10.1038\/s41746-025-01630-1","type":"journal-article","created":{"date-parts":[[2025,4,26]],"date-time":"2025-04-26T14:05:57Z","timestamp":1745676357000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Dual stream transformer for medication state classification in Parkinson\u2019s disease patients using facial videos"],"prefix":"10.1038","volume":"8","author":[{"given":"Vasileios","family":"Skaramagkas","sequence":"first","affiliation":[]},{"given":"Iro","family":"Boura","sequence":"additional","affiliation":[]},{"given":"Georgios","family":"Karamanis","sequence":"additional","affiliation":[]},{"given":"Ioannis","family":"Kyprakis","sequence":"additional","affiliation":[]},{"given":"Dimitrios I.","family":"Fotiadis","sequence":"additional","affiliation":[]},{"given":"Zinovia","family":"Kefalopoulou","sequence":"additional","affiliation":[]},{"given":"Cleanthe","family":"Spanaki","sequence":"additional","affiliation":[]},{"given":"Manolis","family":"Tsiknakis","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,4,26]]},"reference":[{"key":"1630_CR1","doi-asserted-by":"publisher","first-page":"901","DOI":"10.1007\/s00702-017-1686-y","volume":"124","author":"O-B Tysnes","year":"2017","unstructured":"Tysnes, O.-B. & Storstein, A. Epidemiology of Parkinson\u2019s disease. J. Neural Transm. 124, 901\u2013905 (2017).","journal-title":"J. Neural Transm."},{"key":"1630_CR2","doi-asserted-by":"publisher","first-page":"283","DOI":"10.1016\/S0140-6736(23)01419-8","volume":"403","author":"Y Ben-Shlomo","year":"2024","unstructured":"Ben-Shlomo, Y. et al. The epidemiology of Parkinson\u2019s disease. Lancet 403, 283\u2013292 (2024).","journal-title":"Lancet"},{"key":"1630_CR3","doi-asserted-by":"publisher","first-page":"156","DOI":"10.1002\/mds.27063","volume":"33","author":"A Rossi","year":"2018","unstructured":"Rossi, A. et al. Projection of the prevalence of Parkinson\u2019s disease in the coming decades: Revisited. Mov. Disord. Off. J. Mov. Disord. Soc. 33, 156\u2013159 (2018).","journal-title":"Mov. Disord. Off. J. Mov. Disord. Soc."},{"key":"1630_CR4","doi-asserted-by":"publisher","first-page":"939","DOI":"10.1016\/S1474-4422(18)30295-3","volume":"17","author":"ER Dorsey","year":"2018","unstructured":"Dorsey, E. R. Global, regional, and national burden of Parkinson\u2019s disease, 1990-2016: a systematic analysis for the Global Burden of Disease Study 2016. Lancet Neurol. 17, 939\u2013953 (2018).","journal-title":"Lancet Neurol."},{"key":"1630_CR5","doi-asserted-by":"publisher","first-page":"95","DOI":"10.1038\/s41531-024-00712-3","volume":"10","author":"T H\u00e4hnel","year":"2024","unstructured":"H\u00e4hnel, T. et al. Progression subtypes in Parkinson\u2019s disease identified by a data-driven multi cohort analysis. NPJ Parkinsons Dis. 10, 95 (2024).","journal-title":"NPJ Parkinsons Dis."},{"key":"1630_CR6","doi-asserted-by":"publisher","first-page":"328","DOI":"10.1111\/ejn.14094","volume":"49","author":"JC Greenland","year":"2019","unstructured":"Greenland, J. C., Williams-Gray, C. H. & Barker, R. A. The clinical heterogeneity of Parkinson\u2019s disease and its therapeutic implications. Eur. J. Neurosci. 49, 328\u2013338 (2019).","journal-title":"Eur. J. Neurosci."},{"key":"1630_CR7","doi-asserted-by":"publisher","first-page":"525","DOI":"10.3233\/JPD-191633","volume":"9","author":"HV Gupta","year":"2019","unstructured":"Gupta, H. V., Lyons, K. E., Wachter, N. & Pahwa, R. Long term response to levodopa in parkinson\u2019s disease. J. Parkinson\u2019s Dis. 9, 525\u2013529 (2019).","journal-title":"J. Parkinson\u2019s Dis."},{"key":"1630_CR8","doi-asserted-by":"publisher","first-page":"948","DOI":"10.1002\/mds.28406","volume":"36","author":"WRW Martin","year":"2021","unstructured":"Martin, W. R. W. et al. Is levodopa response a valid indicator of parkinson\u2019s disease? Mov. Disord. Off. J. Mov. Disord. Soc. 36, 948\u2013954 (2021).","journal-title":"Mov. Disord. Off. J. Mov. Disord. Soc."},{"key":"1630_CR9","doi-asserted-by":"publisher","first-page":"232","DOI":"10.17294\/2330-0698.1836","volume":"8","author":"S Mantri","year":"2021","unstructured":"Mantri, S. et al. The experience of off periods in parkinson\u2019s disease: descriptions, triggers, and alleviating factors. J. Patient Centered Res. Rev. 8, 232\u2013238 (2021).","journal-title":"J. Patient Centered Res. Rev."},{"key":"1630_CR10","doi-asserted-by":"publisher","first-page":"448","DOI":"10.1016\/S1474-4422(24)00116-9","volume":"23","author":"F Cardoso","year":"2024","unstructured":"Cardoso, F. & Tolosa, E. Fluctuations in Parkinson\u2019s disease: progress and challenges. Lancet Neurol. 23, 448\u2013449 (2024).","journal-title":"Lancet Neurol."},{"key":"1630_CR11","doi-asserted-by":"publisher","first-page":"106890","DOI":"10.1016\/j.clineuro.2021.106890","volume":"209","author":"I Guan","year":"2021","unstructured":"Guan, I. et al. Comparison of the Parkinson\u2019s KinetiGraph to off\/on levodopa response testing: Single center experience. Clin. Neurol. Neurosurg. 209, 106890 (2021).","journal-title":"Clin. Neurol. Neurosurg."},{"key":"1630_CR12","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1038\/s41531-023-00585-y","volume":"9","author":"C Moreau","year":"2023","unstructured":"Moreau, C. et al. Overview on wearable sensors for the management of Parkinson\u2019s disease. npj Parkinsons Dis. 9, 1\u201316 (2023).","journal-title":"npj Parkinsons Dis."},{"key":"1630_CR13","doi-asserted-by":"publisher","first-page":"783","DOI":"10.1007\/s00702-022-02575-5","volume":"130","author":"H Reichmann","year":"2023","unstructured":"Reichmann, H., Klingelhoefer, L. & Bendig, J. The use of wearables for the diagnosis and treatment of Parkinson\u2019s disease. J. Neural Transm. 130, 783\u2013791 (2023).","journal-title":"J. Neural Transm."},{"key":"1630_CR14","doi-asserted-by":"crossref","unstructured":"Kangarloo, T. et al. Acceptability of digital health technologies in early Parkinson\u2019s disease: lessons from WATCH-PD. Front. Digital Health 6, 1435693 (2024).","DOI":"10.3389\/fdgth.2024.1435693"},{"key":"1630_CR15","unstructured":"Overview. Devices for remote monitoring of Parkinson\u2019s disease. Guidance (NICE, 2023)."},{"key":"1630_CR16","doi-asserted-by":"publisher","first-page":"33","DOI":"10.1016\/j.medengphy.2019.03.002","volume":"67","author":"MD Hssayeni","year":"2019","unstructured":"Hssayeni, M. D., Burack, M. A., Jimenez-Shahed, J. & Ghoraani, B. Assessment of response to medication in individuals with Parkinson\u2019s disease. Med. Eng. Phys. 67, 33\u201343 (2019).","journal-title":"Med. Eng. Phys."},{"key":"1630_CR17","doi-asserted-by":"publisher","first-page":"6168","DOI":"10.1109\/JBHI.2024.3423708","volume":"28","author":"M Shuqair","year":"2024","unstructured":"Shuqair, M., Jimenez-Shahed, J. & Ghoraani, B. Reinforcement learning-based adaptive classification for medication state monitoring in parkinson\u2019s disease. IEEE J. Biomed. Health Inform. 28, 6168\u20136179 (2024).","journal-title":"IEEE J. Biomed. Health Inform."},{"key":"1630_CR18","doi-asserted-by":"publisher","first-page":"e8","DOI":"10.2196\/rehab.8335","volume":"5","author":"A Rodr\u00edguez-Molinero","year":"2018","unstructured":"Rodr\u00edguez-Molinero, A. et al. A kinematic sensor and algorithm to detect motor fluctuations in parkinson disease: validation study under real conditions of use. JMIR Rehabil. Assistive Technol. 5, e8 (2018).","journal-title":"JMIR Rehabil. Assistive Technol."},{"key":"1630_CR19","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-020-61789-3","volume":"10","author":"FMJ Pfister","year":"2020","unstructured":"Pfister, F. M. J. et al. High-resolution motor state detection in parkinson\u2019s disease using convolutional neural networks. Sci. Rep. 10, 5860 (2020).","journal-title":"Sci. Rep."},{"key":"1630_CR20","doi-asserted-by":"publisher","first-page":"3720","DOI":"10.1111\/ene.15513","volume":"29","author":"F Sampedro","year":"2022","unstructured":"Sampedro, F., Mart\u00ednez-Horta, S., Horta-Barba, A., Grothe, M. J. & Labrador-Espinosa, M. A. Clinical and structural brain correlates of hypomimia in early-stage Parkinson\u2019s disease. Eur. J. Neurol. 29, 3720\u20133727 (2022).","journal-title":"Eur. J. Neurol."},{"key":"1630_CR21","doi-asserted-by":"publisher","first-page":"2422","DOI":"10.1111\/ene.14452","volume":"27","author":"L Ricciardi","year":"2020","unstructured":"Ricciardi, L. et al. Hypomimia in Parkinson\u2019s disease: an axial sign responsive to levodopa. Eur. J. Neurol. 27, 2422\u20132429 (2020).","journal-title":"Eur. J. Neurol."},{"key":"1630_CR22","doi-asserted-by":"publisher","first-page":"603582","DOI":"10.3389\/fneur.2020.603582","volume":"11","author":"T Maycas-Cepeda","year":"2020","unstructured":"Maycas-Cepeda, T. et al. Hypomimia in parkinson\u2019s disease: what is it telling us? Front. Neurol. 11, 603582 (2020).","journal-title":"Front. Neurol."},{"key":"1630_CR23","doi-asserted-by":"publisher","first-page":"213","DOI":"10.1002\/mdc3.13603","volume":"10","author":"RN Schade","year":"2023","unstructured":"Schade, R. N. et al. A pilot trial of dopamine replacement for dynamic facial expressions in parkinson\u2019s disease. Mov. Disord. Clin. Pract. 10, 213\u2013222 (2023).","journal-title":"Mov. Disord. Clin. Pract."},{"key":"1630_CR24","doi-asserted-by":"crossref","unstructured":"M\u00e4kinen, E. et al. Individual parkinsonian motor signs and striatal dopamine transporter deficiency: a study with [I-123]FP-CIT SPECT. J. Neurol. 266, 826\u2013834 (2019).","DOI":"10.1007\/s00415-019-09202-6"},{"key":"1630_CR25","doi-asserted-by":"publisher","first-page":"e2","DOI":"10.1111\/ene.14483","volume":"28","author":"J Pasquini","year":"2021","unstructured":"Pasquini, J. & Pavese, N. Striatal dopaminergic denervation and hypomimia in Parkinson\u2019s disease. Eur. J. Neurol. 28, e2\u2013e3 (2021).","journal-title":"Eur. J. Neurol."},{"key":"1630_CR26","doi-asserted-by":"publisher","first-page":"589","DOI":"10.3390\/brainsci13040589","volume":"13","author":"V Skaramagkas","year":"2023","unstructured":"Skaramagkas, V. et al. Esee-d: emotional state estimation based on eye-tracking dataset. Brain Sci. 13, 589 (2023).","journal-title":"Brain Sci."},{"key":"1630_CR27","doi-asserted-by":"publisher","first-page":"106989","DOI":"10.1016\/j.cmpb.2022.106989","volume":"224","author":"E Ktistakis","year":"2022","unstructured":"Ktistakis, E. et al. COLET: A dataset for COgnitive workLoad estimation based on eye-tracking. Comput. Methods Prog. Biomed. 224, 106989 (2022).","journal-title":"Comput. Methods Prog. Biomed."},{"key":"1630_CR28","doi-asserted-by":"crossref","unstructured":"Gkikas, S. et al. Multimodal automatic assessment of acute pain through facial videos and heart rate signals utilizing transformer-based architectures. Front. Pain Res. 5, 1372814 (2024).","DOI":"10.3389\/fpain.2024.1372814"},{"key":"1630_CR29","doi-asserted-by":"publisher","first-page":"2399","DOI":"10.1109\/TNSRE.2023.3277749","volume":"31","author":"V Skaramagkas","year":"2023","unstructured":"Skaramagkas, V., Pentari, A., Kefalopoulou, Z. & Tsiknakis, M. Multi-modal deep learning diagnosis of parkinson\u2019s disease-a systematic review. IEEE Trans. Neural Syst. Rehabilit. Eng. 31, 2399\u20132423 (2023).","journal-title":"IEEE Trans. Neural Syst. Rehabilit. Eng."},{"key":"1630_CR30","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1038\/s41746-022-00642-5","volume":"5","author":"M Novotny","year":"2022","unstructured":"Novotny, M. et al. Automated video-based assessment of facial bradykinesia in de-novo Parkinson\u2019s disease. npj Digital Med. 5, 1\u20138 (2022).","journal-title":"npj Digital Med."},{"key":"1630_CR31","first-page":"4192","volume":"2022","author":"B Valenzuela","year":"2022","unstructured":"Valenzuela, B., Arevalo, J., Contreras, W. & Martinez, F. A spatio-temporal hypomimic deep descriptor to discriminate parkinsonian patients. Annu. Int. Conf. IEEE Eng. Med. Biol. Soc. IEEE Eng. Med. Biol. Soc. Annu. Int. Conf. 2022, 4192\u20134195 (2022).","journal-title":"Annu. Int. Conf. IEEE Eng. Med. Biol. Soc. IEEE Eng. Med. Biol. Soc. Annu. Int. Conf."},{"key":"1630_CR32","doi-asserted-by":"crossref","unstructured":"Abrami, A. et al. Automated computer vision assessment of hypomimia in parkinson disease: Proof-of-principle pilot study. J. Med. Internet Res. 23, e21037 (2021).","DOI":"10.2196\/21037"},{"key":"1630_CR33","doi-asserted-by":"publisher","first-page":"1257","DOI":"10.1016\/bs.irn.2017.05.015","volume":"134","author":"N Titova","year":"2017","unstructured":"Titova, N. & Chaudhuri, K. R. Personalized medicine and nonmotor symptoms in parkinson\u2019s disease. Int. Rev. Neurobiol. 134, 1257\u20131281 (2017).","journal-title":"Int. Rev. Neurobiol."},{"key":"1630_CR34","doi-asserted-by":"publisher","first-page":"4845","DOI":"10.1093\/brain\/awad265","volume":"146","author":"N Vijiaratnam","year":"2023","unstructured":"Vijiaratnam, N. & Foltynie, T. How should we be using biomarkers in trials of disease modification in Parkinson\u2019s disease? Brain A J. Neurol. 146, 4845\u20134869 (2023).","journal-title":"Brain A J. Neurol."},{"key":"1630_CR35","doi-asserted-by":"publisher","first-page":"1723","DOI":"10.1212\/WNL.41.11.1723","volume":"41","author":"AJ Hughes","year":"1991","unstructured":"Hughes, A. J., Lees, A. J. & Stern, G. M. Challenge tests to predict the dopaminergic response in untreated Parkinson\u2019s disease. Neurology 41, 1723\u20131725 (1991).","journal-title":"Neurology"},{"key":"1630_CR36","doi-asserted-by":"publisher","first-page":"109","DOI":"10.3390\/brainsci14010109","volume":"14","author":"E Bianchini","year":"2024","unstructured":"Bianchini, E. et al. The story behind the mask: a narrative review on hypomimia in parkinson\u2019s disease. Brain Sci. 14, 109 (2024).","journal-title":"Brain Sci."},{"key":"1630_CR37","doi-asserted-by":"publisher","first-page":"89","DOI":"10.1016\/j.parkreldis.2010.09.005","volume":"17","author":"AN Nisenzon","year":"2011","unstructured":"Nisenzon, A. N. et al. Measurement of patient-centered outcomes in Parkinson\u2019s disease: what do patients really want from their treatment? Parkinsonism Relat. Disord. 17, 89\u201394 (2011).","journal-title":"Parkinsonism Relat. Disord."},{"key":"1630_CR38","doi-asserted-by":"publisher","first-page":"1307","DOI":"10.21037\/atm-21-3457","volume":"9","author":"G Su","year":"2021","unstructured":"Su, G. et al. Detection of hypomimia in patients with Parkinson\u2019s disease via smile videos. Ann. Transl. Med. 9, 1307 (2021).","journal-title":"Ann. Transl. Med."},{"key":"1630_CR39","doi-asserted-by":"publisher","first-page":"1488","DOI":"10.1002\/mds.27772","volume":"34","author":"M Matarazzo","year":"2019","unstructured":"Matarazzo, M., Arroyo-Gallego, T., Montero, P. & Puertas-Mart\u00edn, V. Remote monitoring of treatment response in parkinson\u2019s disease: the habit of typing on a computer. Mov. Disord. Off. J. Mov. Disord. Soc. 34, 1488\u20131495 (2019).","journal-title":"Mov. Disord. Off. J. Mov. Disord. Soc."},{"key":"1630_CR40","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1038\/s41531-021-00227-1","volume":"7","author":"G Di Lazzaro","year":"2021","unstructured":"Di Lazzaro, G. et al. Technology-based therapy-response and prognostic biomarkers in a prospective study of a de novo Parkinson\u2019s disease cohort. Npj Parkinsons Dis. 7, 1\u20137 (2021).","journal-title":"Npj Parkinsons Dis."},{"key":"1630_CR41","doi-asserted-by":"publisher","first-page":"159","DOI":"10.1109\/TBME.2017.2697764","volume":"65","author":"CL Pulliam","year":"2018","unstructured":"Pulliam, C. L. et al. Continuous assessment of levodopa response in parkinson\u2019s disease using wearable motion sensors. IEEE Trans. Bio Med. Eng. 65, 159\u2013164 (2018).","journal-title":"IEEE Trans. Bio Med. Eng."},{"key":"1630_CR42","doi-asserted-by":"publisher","first-page":"765","DOI":"10.1017\/S135561770606111X","volume":"12","author":"D Bowers","year":"2006","unstructured":"Bowers, D. et al. Faces of emotion in Parkinsons disease: micro-expressivity and bradykinesia during voluntary facial expressions. J. Int. Neuropsychological Soc. JINS 12, 765\u2013773 (2006).","journal-title":"J. Int. Neuropsychological Soc. JINS"},{"key":"1630_CR43","doi-asserted-by":"publisher","first-page":"S11","DOI":"10.1002\/mds.20458","volume":"20","author":"J Jankovic","year":"2005","unstructured":"Jankovic, J. Motor fluctuations and dyskinesias in Parkinson\u2019s disease: clinical manifestations. Mov. Disord. Off. J. Mov. Disord. Soc. 20, S11\u201316 (2005).","journal-title":"Mov. Disord. Off. J. Mov. Disord. Soc."},{"key":"1630_CR44","doi-asserted-by":"crossref","unstructured":"Um, T. T. Data augmentation of wearable sensor data for parkinson\u2019s disease monitoring using convolutional neural networks. In: Proceedings of the 19th ACM International Conference on Multimodal Interaction, ICMI \u201917, 216\u2013220 (Association for Computing Machinery, 2017).","DOI":"10.1145\/3136755.3136817"},{"key":"1630_CR45","doi-asserted-by":"publisher","first-page":"44","DOI":"10.1016\/j.parkreldis.2016.09.009","volume":"33","author":"JM Fisher","year":"2016","unstructured":"Fisher, J. M. et al. Unsupervised home monitoring of Parkinson\u2019s disease motor symptoms using body-worn accelerometers. Parkinsonism Relat. Disord. 33, 44\u201350 (2016).","journal-title":"Parkinsonism Relat. Disord."},{"key":"1630_CR46","doi-asserted-by":"publisher","first-page":"S1","DOI":"10.1212\/WNL.0b013e3181a1d44c","volume":"72","author":"CW Olanow","year":"2009","unstructured":"Olanow, C. W., Stern, M. B. & Sethi, K. The scientific and clinical basis for the treatment of Parkinson disease (2009). Neurology 72, S1\u2013136 (2009).","journal-title":"Neurology"},{"key":"1630_CR47","doi-asserted-by":"publisher","first-page":"1591","DOI":"10.1002\/mds.26424","volume":"30","author":"RB Postuma","year":"2015","unstructured":"Postuma, R. B. et al. MDS clinical diagnostic criteria for Parkinson\u2019s disease: MDS-PD Clinical Diagnostic Criteria. Mov. Disord. 30, 1591\u20131601 (2015).","journal-title":"Mov. Disord."},{"key":"1630_CR48","doi-asserted-by":"publisher","first-page":"427","DOI":"10.1212\/WNL.17.5.427","volume":"17","author":"MM Hoehn","year":"1967","unstructured":"Hoehn, M. M. & Yahr, M. D. Parkinsonism: onset, progression and mortality. Neurology 17, 427\u2013442 (1967).","journal-title":"Neurology"},{"key":"1630_CR49","doi-asserted-by":"publisher","first-page":"360","DOI":"10.1017\/S1355617723000747","volume":"30","author":"S Ro\u00dfkopf","year":"2024","unstructured":"Ro\u00dfkopf, S., Wechsler, T. F., Tucha, S. & M\u00fchlberger, A. Effects of facial biofeedback on hypomimia, emotion recognition, and affect in Parkinson\u2019s disease. J. Int. Neuropsychological Soc. 30, 360\u2013369 (2024).","journal-title":"J. Int. Neuropsychological Soc."},{"key":"1630_CR50","doi-asserted-by":"publisher","first-page":"393","DOI":"10.33588\/rn.7011.2019414","volume":"70","author":"R Chiaramonte","year":"2020","unstructured":"Chiaramonte, R. & Bonfiglio, M. Acoustic analysis of voice in Parkinson\u2019s disease: a systematic review of voice disability and meta-analysis of studies. Rev. De. Neurologia 70, 393\u2013405 (2020).","journal-title":"Rev. De. Neurologia"},{"key":"1630_CR51","doi-asserted-by":"publisher","first-page":"1353","DOI":"10.1016\/j.mayocp.2023.03.007","volume":"98","author":"JDS Sara","year":"2023","unstructured":"Sara, J. D. S., Orbelo, D., Maor, E., Lerman, L. O. & Lerman, A. Guess what we can hear-\"novel voice biomarkers for the remote detection of disease. Mayo Clin. Proc. 98, 1353\u20131375 (2023).","journal-title":"Mayo Clin. Proc."},{"key":"1630_CR52","doi-asserted-by":"publisher","first-page":"1499","DOI":"10.1109\/LSP.2016.2603342","volume":"23","author":"K Zhang","year":"2016","unstructured":"Zhang, K., Zhang, Z., Li, Z. & Qiao, Y. Joint face detection and alignment using multitask cascaded convolutional networks. IEEE Signal Process. Lett. 23, 1499\u20131503 (2016).","journal-title":"IEEE Signal Process. Lett."},{"key":"1630_CR53","doi-asserted-by":"publisher","first-page":"187536","DOI":"10.1109\/ACCESS.2024.3470122","volume":"12","author":"T Kumar","year":"2024","unstructured":"Kumar, T., Brennan, R., Mileo, A. & Bendechache, M. Image data augmentation approaches: a comprehensive survey and future directions. IEEE Access 12, 187536\u2013187571 (2024).","journal-title":"IEEE Access"},{"key":"1630_CR54","doi-asserted-by":"crossref","unstructured":"Farneb\u00e4ck, G. Two-frame motion estimation based on polynomial expansion. In: Image Analysis, (eds, Bigun, J. & Gustavsson, T.) 363\u2013370 (Springer, 2003).","DOI":"10.1007\/3-540-45103-X_50"},{"key":"1630_CR55","doi-asserted-by":"publisher","first-page":"699","DOI":"10.1213\/ANE.0b013e31827f53d7","volume":"117","author":"G Divine","year":"2013","unstructured":"Divine, G., Norton, H. J., Hunt, R. & Dienemann, J. A review of analysis and sample size calculation considerations for wilcoxon tests. Anesthesia Analgesia 117, 699\u2013710 (2013).","journal-title":"Anesthesia Analgesia"}],"container-title":["npj Digital Medicine"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.nature.com\/articles\/s41746-025-01630-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s41746-025-01630-1","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s41746-025-01630-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,4,26]],"date-time":"2025-04-26T15:03:24Z","timestamp":1745679804000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.nature.com\/articles\/s41746-025-01630-1"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,4,26]]},"references-count":55,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2025,12]]}},"alternative-id":["1630"],"URL":"https:\/\/doi.org\/10.1038\/s41746-025-01630-1","relation":{},"ISSN":["2398-6352"],"issn-type":[{"type":"electronic","value":"2398-6352"}],"subject":[],"published":{"date-parts":[[2025,4,26]]},"assertion":[{"value":"14 January 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"10 April 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"26 April 2025","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"The authors declare no competing interests.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"226"}}