{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,12]],"date-time":"2026-03-12T17:44:58Z","timestamp":1773337498913,"version":"3.50.1"},"reference-count":22,"publisher":"Springer Science and Business Media LLC","issue":"16","license":[{"start":{"date-parts":[[2024,3,2]],"date-time":"2024-03-02T00:00:00Z","timestamp":1709337600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,3,2]],"date-time":"2024-03-02T00:00:00Z","timestamp":1709337600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Neural Comput &amp; Applic"],"published-print":{"date-parts":[[2024,6]]},"DOI":"10.1007\/s00521-024-09583-4","type":"journal-article","created":{"date-parts":[[2024,3,2]],"date-time":"2024-03-02T09:02:08Z","timestamp":1709370128000},"page":"9361-9374","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":19,"title":["A new deep neuro-fuzzy system for Lyme disease detection and classification using UNet, Inception, and XGBoost model from medical images"],"prefix":"10.1007","volume":"36","author":[{"given":"S. Vishnu","family":"Priyan","sequence":"first","affiliation":[]},{"given":"S.","family":"Dhanasekaran","sequence":"additional","affiliation":[]},{"given":"P. Vivek","family":"Karthick","sequence":"additional","affiliation":[]},{"given":"D.","family":"Silambarasan","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,3,2]]},"reference":[{"key":"9583_CR1","doi-asserted-by":"publisher","first-page":"666554","DOI":"10.3389\/fmed.2021.666554","volume":"8","author":"JR Bobe","year":"2021","unstructured":"Bobe JR, Jutras BL, Horn EJ, Embers ME, Bailey A, Moritz RL, Zhang Y, Soloski MJ, Ostfeld RS, Marconi RT, Aucott J, Ma\u2019ayan A, Keesing F, Lewis K, Ben Mamoun C, Rebman AW, McClune ME, Breitschwerdt EB, Reddy PJ, Maggi R, Yang F, Nemser B, Ozcan A, Garner O, Di Carlo D, Ballard Z, Joung HA, Garcia-Romeu A, Griffiths RR, Baumgarth N, Fallon BA (2021) Recent progress in Lyme disease and remaining challenges. Front Med (Lausanne) 8:666554. https:\/\/doi.org\/10.3389\/fmed.2021.666554","journal-title":"Front Med (Lausanne)"},{"issue":"12","key":"9583_CR2","doi-asserted-by":"publisher","first-page":"e0168613","DOI":"10.1371\/journal.pone.0168613","volume":"11","author":"LA Waddell","year":"2016","unstructured":"Waddell LA, Greig J, Mascarenhas M, Harding S, Lindsay R, Ogden N (2016) The accuracy of diagnostic tests for Lyme disease in humans, a systematic review and meta-analysis of North American research. PLoS ONE 11(12):e0168613. https:\/\/doi.org\/10.1371\/journal.pone.0168613","journal-title":"PLoS ONE"},{"key":"9583_CR3","doi-asserted-by":"publisher","unstructured":"Sharma M, Manjari S, Agrawal E, Keshavan P, Koripella R, Majumdar S, Marcinkiewicz A, Lin Y-P, Agrawal R, Banavali N (2023) The structure of a hibernating ribosome in a Lyme disease pathogen. bioRxiv: the preprint server for biology. https:\/\/doi.org\/10.1101\/2023.04.16.537070","DOI":"10.1101\/2023.04.16.537070"},{"key":"9583_CR4","doi-asserted-by":"crossref","unstructured":"Jose T, Pandiaraj S, Velliangiri S (2021) Investigation of smart methodologies in Lyme disease detection. In: 2021 International conference on computer communication and informatics (ICCCI). IEEE, pp 1\u20135","DOI":"10.1109\/ICCCI50826.2021.9402359"},{"issue":"2","key":"9583_CR5","doi-asserted-by":"publisher","first-page":"150","DOI":"10.7150\/ijms.17763","volume":"14","author":"JD Scott","year":"2017","unstructured":"Scott JD, Foley JE, Anderson JF, Clark KL, Durden LA (2017) Detection of Lyme disease bacterium, Borrelia burgdorferi sensu lato, in blacklegged ticks collected in the Grand River Valley, Ontario, Canada. Int J Med Sci 14(2):150\u2013158. https:\/\/doi.org\/10.7150\/ijms.17763","journal-title":"Int J Med Sci"},{"key":"9583_CR6","doi-asserted-by":"publisher","first-page":"19","DOI":"10.1097\/01.JAA.0000902892.41571.17","volume":"36","author":"K Eckenrode","year":"2023","unstructured":"Eckenrode K (2023) Early identification of Lyme disease complications. JAAPA Off J Am Acad Physician Assist 36:19\u201323. https:\/\/doi.org\/10.1097\/01.JAA.0000902892.41571.17","journal-title":"JAAPA Off J Am Acad Physician Assist"},{"issue":"1","key":"9583_CR7","doi-asserted-by":"publisher","first-page":"229","DOI":"10.1021\/acsnano.9b08151","volume":"14","author":"HA Joung","year":"2020","unstructured":"Joung HA, Ballard ZS, Wu J, Tseng DK, Teshome H, Zhang L, Horn EJ, Arnaboldi PM, Dattwyler RJ, Garner OB, Di Carlo D, Ozcan A (2020) Point-of-care serodiagnostic test for early-stage Lyme disease using a multiplexed paper-based immunoassay and machine learning. ACS Nano 14(1):229\u2013240. https:\/\/doi.org\/10.1021\/acsnano.9b08151","journal-title":"ACS Nano"},{"key":"9583_CR8","doi-asserted-by":"publisher","DOI":"10.7759\/cureus.37374","author":"J Palmer","year":"2023","unstructured":"Palmer J, Ghuman K, Suhail K, Nagib N (2023) Atrial flutter and left hemidiaphragmatic paralysis in the setting of Lyme disease. Cureus. https:\/\/doi.org\/10.7759\/cureus.37374","journal-title":"Cureus"},{"key":"9583_CR9","doi-asserted-by":"publisher","first-page":"13519","DOI":"10.1111\/srt.13519","volume":"29","author":"G Ali","year":"2023","unstructured":"Ali G, Anwar M, Nauman M, Faheem M, Rashid J (2023) Lyme rashes disease classification using deep feature fusion technique. Skin Res Technol 29:13519. https:\/\/doi.org\/10.1111\/srt.13519","journal-title":"Skin Res Technol"},{"key":"9583_CR10","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1109\/JTEHM.2021.3137956","volume":"10","author":"S Akbarian","year":"2022","unstructured":"Akbarian S et al (2022) A computer vision approach to identifying ticks related to Lyme disease. IEEE J Transl Eng Health Med 10:1\u20138. https:\/\/doi.org\/10.1109\/JTEHM.2021.3137956","journal-title":"IEEE J Transl Eng Health Med"},{"key":"9583_CR11","doi-asserted-by":"publisher","DOI":"10.1093\/cid\/ciad307","author":"I Forrest","year":"2023","unstructured":"Forrest I, O\u2019Neal A, Pedra J, Do R (2023) Cholesterol contributes to risk, severity, and machine learning-driven diagnosis of Lyme disease. Clin Infect Dis Off Publ Infect Dis Soc Am. https:\/\/doi.org\/10.1093\/cid\/ciad307","journal-title":"Clin Infect Dis Off Publ Infect Dis Soc Am"},{"key":"9583_CR12","unstructured":"Hossain S, de Herve JDG, Hassan MS, Martineau D, Petrosyan E, Corbain V, Beytout J, Lebert I, Baux E, Cazorla C, Eldin C, Hansmann Y, Patrat-Delon S, Prazuck T, Raffetin A, Tattevin P, Vourc'H G, Lesens O, Nguifo EM (2021) Benchmarking convolutional neural networks for diagnosing Lyme disease from images"},{"key":"9583_CR13","doi-asserted-by":"crossref","unstructured":"Jacob D, Nankar O, Gite S, Patil S, Kotecha K (2022) Lyme disease detection using progressive resizing and self-supervised learning algorithmslyme disease detection using progressive resizing and self-supervised learning algorithms","DOI":"10.2139\/ssrn.4059738"},{"key":"9583_CR14","doi-asserted-by":"publisher","first-page":"92","DOI":"10.1038\/s43856-022-00127-2","volume":"2","author":"V Servellita","year":"2022","unstructured":"Servellita V, Bouquet J, Rebman A, Yang T, Samayoa E, Miller S, Stone M, Lanteri M, Busch M, Tang P, Morshed M, Soloski M, Aucott J, Chiu C (2022) A diagnostic classifier for gene expression-based identification of early Lyme disease. Commun Med 2:92. https:\/\/doi.org\/10.1038\/s43856-022-00127-2","journal-title":"Commun Med"},{"key":"9583_CR15","unstructured":"https:\/\/www.kaggle.com\/datasets\/sshikamaru\/lyme-disease-rashes Accessed on 22nd February 2023"},{"key":"9583_CR16","doi-asserted-by":"publisher","unstructured":"Likhitha S, Baskar R (2022) Skin cancer segmentation using R-CNN comparing with inception V3 for better accuracy. In: 2022 11th international conference on system modeling & advancement in research trends (SMART), Moradabad, India. pp 1293\u20131297. https:\/\/doi.org\/10.1109\/SMART55829.2022.10047686","DOI":"10.1109\/SMART55829.2022.10047686"},{"key":"9583_CR17","doi-asserted-by":"publisher","unstructured":"Carvajal DC, Delgado BM, Ibarra DG, Ariza LC (2022) Skin cancer classification in dermatological images based on a dense hybrid algorithm. In: 2022 IEEE XXIX international conference on electronics, electrical engineering and computing (INTERCON), Lima, Peru. pp 1\u20134. https:\/\/doi.org\/10.1109\/INTERCON55795.2022.9870129","DOI":"10.1109\/INTERCON55795.2022.9870129"},{"key":"9583_CR18","doi-asserted-by":"publisher","unstructured":"Rautela K, Kumar D, Kumar V (2022) Detection and localization of breast lesion with VGG19 optimized vision transformer. In: 2022 4th international conference on artificial intelligence and speech technology (AIST), Delhi, India. pp 1\u20134. https:\/\/doi.org\/10.1109\/AIST55798.2022.10065355","DOI":"10.1109\/AIST55798.2022.10065355"},{"key":"9583_CR19","doi-asserted-by":"publisher","unstructured":"Prasad CR, Arun B, Amulya S, Abboju P, Kollem S, Yalabaka S (2023) Breast cancer classification using CNN with transfer learning models. In: 2023 International conference for advancement in technology (ICONAT), Goa, India. pp 1\u20135. https:\/\/doi.org\/10.1109\/ICONAT57137.2023.10080148","DOI":"10.1109\/ICONAT57137.2023.10080148"},{"key":"9583_CR20","doi-asserted-by":"publisher","unstructured":"Hemalatha K, Vetriselvi V (2022) Deep learning based classification of cervical cancer using transfer learning. In: 2022 International conference on electronic systems and intelligent computing (ICESIC), Chennai, India. pp 134\u2013139. https:\/\/doi.org\/10.1109\/ICESIC53714.2022.9783560","DOI":"10.1109\/ICESIC53714.2022.9783560"},{"key":"9583_CR21","doi-asserted-by":"publisher","first-page":"100846","DOI":"10.1016\/j.measen.2023.100846","volume":"29","author":"V Mandala","year":"2023","unstructured":"Mandala V, Senthilnathan T, Suganyadevi S, Gobhinat S, Selvaraj D, Dhanapal R (2023) An optimized back propagation neural network for automated evaluation of health condition using sensor data. Meas Sens 29:100846","journal-title":"Meas Sens"},{"key":"9583_CR22","doi-asserted-by":"publisher","DOI":"10.1080\/10255842.2023.2281277","author":"S D","year":"2023","unstructured":"Dhanasekaran S, Silambarasan D, Vivek Karthick P, Sudhakar K (2023) Enhancing pancreatic cancer classification through dynamic weighted ensemble: a game theory approach. Comput Methods Biomech Biomed Eng. https:\/\/doi.org\/10.1080\/10255842.2023.2281277","journal-title":"Comput Methods Biomech Biomed Eng"}],"container-title":["Neural Computing and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-024-09583-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00521-024-09583-4\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-024-09583-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,5,11]],"date-time":"2024-05-11T05:12:37Z","timestamp":1715404357000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00521-024-09583-4"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,3,2]]},"references-count":22,"journal-issue":{"issue":"16","published-print":{"date-parts":[[2024,6]]}},"alternative-id":["9583"],"URL":"https:\/\/doi.org\/10.1007\/s00521-024-09583-4","relation":{},"ISSN":["0941-0643","1433-3058"],"issn-type":[{"value":"0941-0643","type":"print"},{"value":"1433-3058","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,3,2]]},"assertion":[{"value":"25 July 2023","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"5 February 2024","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"2 March 2024","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}