{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,26]],"date-time":"2025-03-26T10:53:56Z","timestamp":1742986436218,"version":"3.40.3"},"publisher-location":"Cham","reference-count":25,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030845315"},{"type":"electronic","value":"9783030845322"}],"license":[{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021]]},"DOI":"10.1007\/978-3-030-84532-2_27","type":"book-chapter","created":{"date-parts":[[2021,8,8]],"date-time":"2021-08-08T23:03:52Z","timestamp":1628463832000},"page":"301-311","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["AI in Skin Cancer Detection"],"prefix":"10.1007","author":[{"given":"Haya","family":"Al-Askar","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rasul","family":"Almurshedi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jamila","family":"Mustafina","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dhiya","family":"Al-Jumeily","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Abir","family":"Hussain","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2021,8,9]]},"reference":[{"key":"27_CR1","unstructured":"Alasadi, A.H.H., AL-Safy, B.M.R.: Early Detection and Classification of Melanoma Skin Cancer. LAP LAMBERT Academic Publishing, Sunnyvale (2016)"},{"key":"27_CR2","doi-asserted-by":"publisher","first-page":"38306","DOI":"10.1109\/ACCESS.2019.2906241","volume":"7","author":"MA Albahar","year":"2019","unstructured":"Albahar, M.A.: Skin lesion classification using convolutional neural network with novel regularizer. IEEE Access 7, 38306\u201338313 (2019)","journal-title":"IEEE Access"},{"issue":"8","key":"27_CR3","doi-asserted-by":"publisher","first-page":"1020","DOI":"10.1109\/TBME.2003.814534","volume":"50","author":"DG Beetner","year":"2003","unstructured":"Beetner, D.G., Kapoor, S., Manjunath, S., Zhou, X., Stoecker, W.V.: Differentiation among basal cell carcinoma, benign lesions, and normal skin using electric impedance. IEEE Trans. Biomed. Eng. 50(8), 1020\u20131025 (2003)","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"27_CR4","doi-asserted-by":"crossref","unstructured":"Chatterjee S., Dey D., Munshi, S.: Mathematical morphology aided shape, texture and colour feature extraction from skin lesion for identification of malignant melanoma. In: International Conference on Condition Assessment Techniques in Electrical Systems (CATCON), pp. 200\u2013203 (2015)","DOI":"10.1109\/CATCON.2015.7449534"},{"issue":"9","key":"27_CR5","doi-asserted-by":"publisher","first-page":"19186","DOI":"10.3390\/ijms140919186","volume":"14","author":"S-T Chou","year":"2013","unstructured":"Chou, S.-T., Chang, W.-L., Chang, C.-T., Hsu, S.-L., Lin, Y.-C., Shih, Y.: Cinnamomum cassia essential oil inhibits \u03b1-msh-induced melanin production and oxidative stress in murine b16 melanoma cells. Int. J. Mol. Sci. 14(9), 19186\u201319201 (2013)","journal-title":"Int. J. Mol. Sci."},{"issue":"4\/5","key":"27_CR6","doi-asserted-by":"publisher","first-page":"5","DOI":"10.1147\/JRD.2017.2708299","volume":"61","author":"NC Codella","year":"2017","unstructured":"Codella, N.C., et al.: Deep learning ensembles for melanoma recognition in dermoscopy images. IBM J. Res. Dev. 61(4\/5), 5\u20131 (2017)","journal-title":"IBM J. Res. Dev."},{"key":"27_CR7","doi-asserted-by":"crossref","unstructured":"Darvin M., Klemp M., Weinigel M., Meinke M., K\u00f6nig K., Lademann, J.: In vivo imaging for detection and discrimination of actinic keratosis and squamous cell carcinoma from healthy human skin using two-photon tomography. In: International Conference Laser Optics (LO), pp. S2\u201320 (2016)","DOI":"10.1109\/LO.2016.7549987"},{"issue":"14","key":"27_CR8","doi-asserted-by":"publisher","first-page":"2003","DOI":"10.1016\/S0959-8049(99)00283-X","volume":"35","author":"F De Gruijl","year":"1999","unstructured":"De Gruijl, F.: Skin cancer and solar uv radiation. Eur. J. Cancer 35(14), 2003\u20132009 (1999)","journal-title":"Eur. J. Cancer"},{"key":"27_CR9","doi-asserted-by":"crossref","unstructured":"Ekimci, G.D., Onak, G., Karaman, O., Ercan, U.K.: Assessment of direct and fluid-mediated cold atmospheric plasma treatment eficacy on squamous cell carcinoma. In: Medical Technologies Congress (TIPTEKNO), pp. 1\u20134 (2019)","DOI":"10.1109\/TIPTEKNO.2019.8895138"},{"key":"27_CR10","unstructured":"Eltayef, K.A.A.: Segmentation and lesion detection in dermoscopic images. PhD thesis, Brunel University London (2017)"},{"issue":"7639","key":"27_CR11","doi-asserted-by":"publisher","first-page":"115","DOI":"10.1038\/nature21056","volume":"542","author":"A Esteva","year":"2017","unstructured":"Esteva, A., et al.: Dermatologist-level classification of skin cancer with deep neural networks. Nature 542(7639), 115\u2013118 (2017)","journal-title":"Nature"},{"issue":"1","key":"27_CR12","doi-asserted-by":"publisher","first-page":"117","DOI":"10.1136\/amiajnl-2012-001145","volume":"20","author":"G Hripcsak","year":"2013","unstructured":"Hripcsak, G., Albers, D.J.: Next-generation phenotyping of electronic health records. J. Am. Med. Inform. Assoc. 20(1), 117\u2013121 (2013)","journal-title":"J. Am. Med. Inform. Assoc."},{"issue":"8","key":"27_CR13","doi-asserted-by":"publisher","first-page":"1777","DOI":"10.1109\/TMI.2019.2894349","volume":"38","author":"S Hussein","year":"2019","unstructured":"Hussein, S., Kandel, P., Bolan, C.W., Wallace, M.B., Bagci, U.: Lung and pancreatic tumor characterization in the deep learning era: novel supervised and unsupervised learning approaches. IEEE Trans. Med. Imaging 38(8), 1777\u20131787 (2019)","journal-title":"IEEE Trans. Med. Imaging"},{"issue":"9","key":"27_CR14","doi-asserted-by":"publisher","first-page":"742","DOI":"10.1016\/j.compbiomed.2011.06.010","volume":"41","author":"AG Isasi","year":"2011","unstructured":"Isasi, A.G., Zapirain, B.G., Zorrilla, A.M.: Melanomas non-invasive diagnosis application based on the abcd rule and pattern recognition image processing algorithms. Comput. Biol. Med. 41(9), 742\u2013755 (2011)","journal-title":"Comput. Biol. Med."},{"key":"27_CR15","unstructured":"Kanimozhi T., Murthi, A.: Computer aided melanoma skin cancer detection using artificial neural network classifier. Singaporean J. Sci. Res. (SJSR), J. Sel. Areas Microelectron. (JSAM) 8(2), 35\u201342 (2016)"},{"key":"27_CR16","doi-asserted-by":"crossref","unstructured":"Kasmi, R., Mokrani, K.: Classification of malignant melanoma and benign skin lesions: implementation of automatic abcd rule. IET Image Process.10(6), 448\u2013455 (2016)","DOI":"10.1049\/iet-ipr.2015.0385"},{"key":"27_CR17","unstructured":"Lopez, A.R., Giro-i Nieto, X., Burdick, J., Marques, O.: Skin lesion classification from dermoscopic images using deep learning techniques. In: 13th IASTED International Conference on Biomedical Engineering (BioMed), pp. 49\u201354 (2017)"},{"issue":"15","key":"27_CR18","doi-asserted-by":"publisher","first-page":"e6258","DOI":"10.1097\/MD.0000000000006258","volume":"96","author":"K Mahendraraj","year":"2017","unstructured":"Mahendraraj, K., Sidhu, K., Lau, C.S.M., McRoy, G.J., Chamberlain, R.S., Smith, F.O.: Malignant melanoma in African\u2013Americans: a population-based clinical outcomes study involving 1106 African\u2013American patients from the surveillance, epidemiology, and end result (SEER) database (1988\u20132011). Medicine 96(15), e6258 (2017)","journal-title":"Medicine"},{"key":"27_CR19","series-title":"IFMBE Proceedings","doi-asserted-by":"publisher","first-page":"832","DOI":"10.1007\/978-3-319-19387-8_204","volume-title":"World Congress on Medical Physics and Biomedical Engineering, June 7\u201312, 2015, Toronto, Canada","author":"C Mar\u00edn","year":"2015","unstructured":"Mar\u00edn, C., Alf\u00e9rez, G.H., C\u00f3rdova, J., Gonz\u00e1lez, V.: Detection of melanoma through image recognition and artificial neural networks. In: Jaffray, D.A. (ed.) World Congress on Medical Physics and Biomedical Engineering, June 7\u201312, 2015, Toronto, Canada. IP, vol. 51, pp. 832\u2013835. Springer, Cham (2015). https:\/\/doi.org\/10.1007\/978-3-319-19387-8_204"},{"key":"27_CR20","unstructured":"Mishra, N.K., Celebi, M.E.: An overview of melanoma detection in dermoscopy images using image processing and machine learning. arXiv preprint arXiv:1601.07843 (2016)"},{"key":"27_CR21","doi-asserted-by":"crossref","unstructured":"Nasr-Esfahani, E., et al.: Melanoma detection by analysis of clinical images using convolutional neural network. In: 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), pp. 1373\u20131376 (2016)","DOI":"10.1109\/EMBC.2016.7590963"},{"issue":"8","key":"27_CR22","doi-asserted-by":"publisher","first-page":"1085","DOI":"10.1080\/02713683.2017.1297997","volume":"42","author":"T Nayman","year":"2017","unstructured":"Nayman, T., Bostan, C., Logan, P., Burnier, M.N., Jr.: Uveal melanoma risk factors: a systematic review of meta-analyses. Curr. Eye Res. 42(8), 1085\u20131093 (2017)","journal-title":"Curr. Eye Res."},{"issue":"3","key":"27_CR23","doi-asserted-by":"publisher","first-page":"219","DOI":"10.1109\/TNB.2018.2837622","volume":"17","author":"Q Suo","year":"2018","unstructured":"Suo, Q., et al.: Deep patient similarity learning for personalized healthcare. IEEE Trans. Nanobiosci. 17(3), 219\u2013227 (2018)","journal-title":"IEEE Trans. Nanobiosci."},{"key":"27_CR24","doi-asserted-by":"crossref","unstructured":"Waheed, Z., Waheed, A., Zafar, M., Riaz, F.: An efficient machine learning approach for the detection of melanoma using dermoscopic images. In: International Conference on Communication, Computing and Digital Systems (C-CODE), pp. 316\u2013319 (2017)","DOI":"10.1109\/C-CODE.2017.7918949"},{"key":"27_CR25","doi-asserted-by":"crossref","unstructured":"Wang, Y., Cai, J., Louie, D.C., Lui, H., Lee, T.K., Wang, Z.J.: Classifying melanoma and seborrheic keratosis automatically with polarization speckle imaging. In: IEEE Global Conference on Signal and Information Processing (GlobalSIP), pp. 1\u20134 (2019)","DOI":"10.1109\/GlobalSIP45357.2019.8969331"}],"container-title":["Lecture Notes in Computer Science","Intelligent Computing Theories and Application"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-84532-2_27","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,8,8]],"date-time":"2021-08-08T23:09:00Z","timestamp":1628464140000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-84532-2_27"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021]]},"ISBN":["9783030845315","9783030845322"],"references-count":25,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-84532-2_27","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2021]]},"assertion":[{"value":"9 August 2021","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICIC","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Intelligent Computing","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Shenzhen","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"China","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2021","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"12 August 2021","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"15 August 2021","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"17","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"icic2021a","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.ic-icc.cn\/2021\/index.htm","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}