{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,9,15]],"date-time":"2024-09-15T15:23:17Z","timestamp":1726413797920},"reference-count":84,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/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":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Med Syst"],"published-print":{"date-parts":[[2021,1]]},"DOI":"10.1007\/s10916-020-01679-3","type":"journal-article","created":{"date-parts":[[2021,1,6]],"date-time":"2021-01-06T11:04:29Z","timestamp":1609931069000},"update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["An Integrated Platform for Skin Cancer Heterogenous and Multilayered Data Management"],"prefix":"10.1007","volume":"45","author":[{"ORCID":"http:\/\/orcid.org\/0000-0003-2860-399X","authenticated-orcid":false,"given":"Ilias","family":"Maglogiannis","sequence":"first","affiliation":[]},{"ORCID":"http:\/\/orcid.org\/0000-0003-4631-5246","authenticated-orcid":false,"given":"Georgia","family":"Kontogianni","sequence":"additional","affiliation":[]},{"ORCID":"http:\/\/orcid.org\/0000-0003-3896-4270","authenticated-orcid":false,"given":"Olga","family":"Papadodima","sequence":"additional","affiliation":[]},{"given":"Haralampos","family":"Karanikas","sequence":"additional","affiliation":[]},{"given":"Antonis","family":"Billiris","sequence":"additional","affiliation":[]},{"ORCID":"http:\/\/orcid.org\/0000-0003-2078-0844","authenticated-orcid":false,"given":"Aristotelis","family":"Chatziioannou","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2021,1,6]]},"reference":[{"issue":"2","key":"1679_CR1","doi-asserted-by":"crossref","first-page":"172","DOI":"10.1007\/s11892-012-0350-z","volume":"13","author":"PJ O\u2019Connor","year":"2013","unstructured":"P. J. O\u2019Connor, J. R. Desai, J. C. Butler, E. O. Kharbanda, and J. M. Sperl-Hillen, \u201cCurrent status and future prospects for electronic point-of-care clinical decision support in diabetes care,\u201d Current diabetes reports, vol. 13, no. 2, pp. 172\u2013176, 2013.","journal-title":"Current diabetes reports"},{"issue":"3","key":"1679_CR2","doi-asserted-by":"crossref","first-page":"481","DOI":"10.1111\/j.1365-2133.2005.06386.x","volume":"152","author":"E De Vries","year":"2005","unstructured":"E. De Vries, V. De Poll-Franse, W. Louwman, F. De Gruijl, and J. Coebergh, \u201cPredictions of skin cancer incidence in the Netherlands up to 2015,\u201d British Journal of Dermatology, vol. 152, no. 3, pp. 481\u2013488, 2005.","journal-title":"British Journal of Dermatology"},{"issue":"21","key":"1679_CR3","first-page":"591","volume":"64","author":"GP Guy","year":"2015","unstructured":"G. P. Guy et al., \u201cVital signs: melanoma incidence and mortality trends and projections - United States, 1982\u20132030,\u201d MMWR Morb. Mortal. Wkly. Rep., vol. 64, no. 21, pp. 591\u2013596, 2015.","journal-title":"MMWR Morb. Mortal. Wkly. Rep."},{"issue":"92","key":"1679_CR4","first-page":"101","volume":"17","author":"AM Bailey","year":"2014","unstructured":"A. M. Bailey et al., \u201cImplementation of biomarker-driven cancer therapy: existing tools and remaining gaps,\u201d Discovery medicine, vol. 17, no. 92, p. 101, 2014.","journal-title":"Discovery medicine"},{"issue":"2","key":"1679_CR5","doi-asserted-by":"publisher","first-page":"144","DOI":"10.1111\/j.1755-148X.2012.00975.x","volume":"25","author":"K Dutton-Regester","year":"2012","unstructured":"K. Dutton-Regester and N. K. Hayward, \u201cReviewing the somatic genetics of melanoma: from current to future analytical approaches,\u201d Pigment cell & melanoma research, vol. 25, no. 2, pp. 144\u201354, 2012, https:\/\/doi.org\/10.1111\/j.1755-148X.2012.00975.x.","journal-title":"Pigment cell & melanoma research"},{"issue":"5","key":"1679_CR6","doi-asserted-by":"crossref","first-page":"442","DOI":"10.1038\/ng.810","volume":"43","author":"X Wei","year":"2011","unstructured":"X. Wei et al., \u201cExome sequencing identifies GRIN2A as frequently mutated in melanoma,\u201d Nature genetics, vol. 43, no. 5, pp. 442\u2013446, 2011.","journal-title":"Nature genetics"},{"issue":"9","key":"1679_CR7","doi-asserted-by":"publisher","first-page":"1006","DOI":"10.1038\/ng.2359","volume":"44","author":"M Krauthammer","year":"2012","unstructured":"M. Krauthammer et al., \u201cExome sequencing identifies recurrent somatic RAC1 mutations in melanoma,\u201d Nature genetics, vol. 44, no. 9, pp. 1006\u201314, 2012, https:\/\/doi.org\/10.1038\/ng.2359.","journal-title":"Nature genetics"},{"issue":"2","key":"1679_CR8","doi-asserted-by":"publisher","first-page":"251","DOI":"10.1016\/j.cell.2012.06.024","volume":"150","author":"E Hodis","year":"2012","unstructured":"E. Hodis et al., \u201cA landscape of driver mutations in melanoma,\u201d Cell, vol. 150, no. 2, pp. 251\u201363, 2012, https:\/\/doi.org\/10.1016\/j.cell.2012.06.024.","journal-title":"Cell"},{"doi-asserted-by":"publisher","unstructured":"\u201cGenomic Classification of Cutaneous Melanoma,\u201d Cell, vol. 161, no. 7, pp. 1681\u201396, 2015, https:\/\/doi.org\/10.1016\/j.cell.2015.05.044.","key":"1679_CR9","DOI":"10.1016\/j.cell.2015.05.044"},{"issue":"1","key":"1679_CR10","doi-asserted-by":"crossref","first-page":"4","DOI":"10.1186\/s13336-015-0019-3","volume":"5","author":"C Castaneda","year":"2015","unstructured":"C. Castaneda et al., \u201cClinical decision support systems for improving diagnostic accuracy and achieving precision medicine,\u201d Journal of clinical bioinformatics, vol. 5, no. 1, p. 4, 2015.","journal-title":"Journal of clinical bioinformatics"},{"issue":"3","key":"1679_CR11","doi-asserted-by":"crossref","first-page":"382","DOI":"10.3122\/jabfm.2015.03.140248","volume":"28","author":"L Kuhn","year":"2015","unstructured":"L. Kuhn et al., \u201cPlanning for action: the impact of an asthma action plan decision support tool integrated into an electronic health record (EHR) at a large health care system,\u201d The Journal of the American Board of Family Medicine, vol. 28, no. 3, pp. 382\u2013393, 2015.","journal-title":"The Journal of the American Board of Family Medicine"},{"doi-asserted-by":"crossref","unstructured":"W. Ceusters and B. Smith, \u201cSemantic Interoperability in Healthcare State of the Art in the US,\u201d New York State Center of Excellence in Bioinformatics and Life Sciences Ontology Research Group, pp. 1\u201333, 2010.","key":"1679_CR12","DOI":"10.3233\/SW-2010-0014"},{"doi-asserted-by":"crossref","unstructured":"C. Hahn, S. Jacobi, and D. Raber, \u201cEnhancing the interoperability between multiagent systems and service-oriented architectures through a model-driven approach,\u201d 2010, vol. 2, pp. 415\u2013422.","key":"1679_CR13","DOI":"10.1109\/WI-IAT.2010.217"},{"unstructured":"World Wide Web Consortium, 2012. 2012.","key":"1679_CR14"},{"issue":"6","key":"1679_CR15","doi-asserted-by":"crossref","first-page":"59","DOI":"10.1145\/508448.508475","volume":"45","author":"J Bacon","year":"2002","unstructured":"J. Bacon and K. Moody, \u201cToward open, secure, widely distributed services,\u201d Communications of the ACM, vol. 45, no. 6, pp. 59\u201364, 2002.","journal-title":"Communications of the ACM"},{"unstructured":"H. Catalyst, Late-Binding Data Warehouse, Health Catalyst..","key":"1679_CR16"},{"unstructured":"Diving in: Navigating a data lake for predictive care Patient Data Intelligence fo Next-Generation Care Delivery.","key":"1679_CR17"},{"unstructured":"M. M., \u201cThe Difference Between Data, Analytics, and Insights,\u201d Localytics, Dec. 2016. http:\/\/info.localytics.com\/blog\/difference-between-data-analytics-insights.","key":"1679_CR18"},{"issue":"2","key":"1679_CR19","doi-asserted-by":"crossref","first-page":"227","DOI":"10.1016\/j.annemergmed.2015.06.024","volume":"67","author":"AT Janke","year":"2016","unstructured":"A. T. Janke, D. L. Overbeek, K. E. Kocher, and P. D. Levy, \u201cExploring the potential of predictive analytics and big data in emergency care,\u201d Annals of emergency medicine, vol. 67, no. 2, pp. 227\u2013236, 2016.","journal-title":"Annals of emergency medicine"},{"doi-asserted-by":"crossref","unstructured":"A. Holzinger and I. Jurisica, \u201cKnowledge discovery and data mining in biomedical informatics: The future is in integrative, interactive machine learning solutions,\u201d in Interactive knowledge discovery and data mining in biomedical informatics, Springer, 2014, pp. 1\u201318.","key":"1679_CR20","DOI":"10.1007\/978-3-662-43968-5_1"},{"issue":"5","key":"1679_CR21","doi-asserted-by":"publisher","first-page":"479","DOI":"10.1023\/A:1016413418549","volume":"26","author":"M \u0160progar","year":"2002","unstructured":"M. \u0160progar, M. Leni\u010d, and S. Alayon, \u201cEvolution in Medical Decision Making,\u201d Journal of Medical Systems, vol. 26, no. 5, pp. 479\u2013489, 2002, https:\/\/doi.org\/10.1023\/A:1016413418549.","journal-title":"Journal of Medical Systems"},{"doi-asserted-by":"crossref","unstructured":"F. Wang, L. S. Docherty, K. J. Turner, M. Kolberg, and E. H. Magill, \u201cServices and policies for care at home,\u201d 2006, pp. 1\u201310.","key":"1679_CR22","DOI":"10.1109\/PCTHEALTH.2006.361701"},{"issue":"3","key":"1679_CR23","doi-asserted-by":"crossref","first-page":"293","DOI":"10.1586\/17512433.2014.905201","volume":"7","author":"NT Issa","year":"2014","unstructured":"N. T. Issa, S. W. Byers, and S. Dakshanamurthy, \u201cBig data: the next frontier for innovation in therapeutics and healthcare,\u201d Expert review of clinical pharmacology, vol. 7, no. 3, pp. 293\u2013298, 2014.","journal-title":"Expert review of clinical pharmacology"},{"issue":"3","key":"1679_CR24","doi-asserted-by":"crossref","first-page":"31","DOI":"10.1007\/s10916-015-0225-3","volume":"39","author":"T Goudas","year":"2015","unstructured":"T. Goudas and I. Maglogiannis, \u201cAn advanced image analysis tool for the quantification and characterization of breast cancer in microscopy images,\u201d Journal of medical systems, vol. 39, no. 3, p. 31, 2015.","journal-title":"Journal of medical systems"},{"issue":"12","key":"1679_CR25","doi-asserted-by":"crossref","first-page":"1563","DOI":"10.1001\/archderm.134.12.1563","volume":"134","author":"G Argenziano","year":"1998","unstructured":"G. Argenziano, G. Fabbrocini, P. Carli, V. De Giorgi, E. Sammarco, and M. Delfino, \u201cEpiluminescence microscopy for the diagnosis of doubtful melanocytic skin lesions. Comparison of the ABCD rule of dermatoscopy and a new 7-point checklist based on pattern analysis,\u201d Archives of dermatology, vol. 134, no. 12, pp. 1563\u201370, 1998.","journal-title":"Archives of dermatology"},{"doi-asserted-by":"crossref","unstructured":"G. Betta, G. Di Leo, G. Fabbrocini, A. Paolillo, and M. Scalvenzi, \u201cAutomated Application of the \u20187-point checklist\u2019 Diagnosis Method for Skin Lesions: Estimation of Chromatic and Shape Parameters,\u201d 2005, vol. 3, pp. 1818\u20131822.","key":"1679_CR26","DOI":"10.1109\/IMTC.2005.1604486"},{"doi-asserted-by":"crossref","unstructured":"M. Ogorza\u0142ek, L. Nowak, G. Surowka, and A. Alekseenko, \u201cMelanoma in the clinic\u2014diagnosis, management and complications of malignancy,\u201d Modern Techniques for Computer-Aided Melanoma Diagnosis, 2011.","key":"1679_CR27","DOI":"10.5772\/23388"},{"issue":"5","key":"1679_CR28","doi-asserted-by":"publisher","first-page":"455","DOI":"10.1023\/B:JOMS.0000041172.70027.a0","volume":"28","author":"I Maglogiannis","year":"2004","unstructured":"I. Maglogiannis, \u201cDesign and Implementation of a Calibrated Store and Forward Imaging System for Teledermatology,\u201d Journal of Medical Systems, vol. 28, no. 5, pp. 455\u2013467, 2004, https:\/\/doi.org\/10.1023\/B:JOMS.0000041172.70027.a0.","journal-title":"Journal of Medical Systems"},{"issue":"5","key":"1679_CR29","doi-asserted-by":"crossref","first-page":"721","DOI":"10.1109\/TITB.2009.2017529","volume":"13","author":"I Maglogiannis","year":"2009","unstructured":"I. Maglogiannis and C. N. Doukas, \u201cOverview of advanced computer vision systems for skin lesions characterization,\u201d IEEE transactions on information technology in biomedicine, vol. 13, no. 5, pp. 721\u2013733, 2009.","journal-title":"IEEE transactions on information technology in biomedicine"},{"issue":"4","key":"1679_CR30","doi-asserted-by":"crossref","first-page":"402","DOI":"10.1111\/j.1365-4632.2006.02726.x","volume":"45","author":"AG Manousaki","year":"2006","unstructured":"A. G. Manousaki et al., \u201cA simple digital image processing system to aid in melanoma diagnosis in an everyday melanocytic skin lesion unit. A preliminary report,\u201d International journal of dermatology, vol. 45, no. 4, pp. 402\u2013410, 2006.","journal-title":"International journal of dermatology"},{"issue":"4","key":"1679_CR31","doi-asserted-by":"crossref","first-page":"57","DOI":"10.1109\/51.107171","volume":"10","author":"SE Umbaugh","year":"1991","unstructured":"S. E. Umbaugh, R. H. Moss, and W. V. Stoecker, \u201cApplying artificial intelligence to the identification of variegated coloring in skin tumors,\u201d IEEE engineering in medicine and biology magazine, vol. 10, no. 4, pp. 57\u201362, 1991.","journal-title":"IEEE engineering in medicine and biology magazine"},{"issue":"11","key":"1679_CR32","doi-asserted-by":"publisher","first-page":"177","DOI":"10.1007\/s10916-015-0354-8","volume":"39","author":"M Filho","year":"2015","unstructured":"M. Filho, Z. Ma, and J. M. R. S. Tavares, \u201cA Review of the Quantification and Classification of Pigmented Skin Lesions: From Dedicated to Hand-Held Devices,\u201d J Med Syst, vol. 39, no. 11, p. 177, 2015, https:\/\/doi.org\/10.1007\/s10916-015-0354-8.","journal-title":"J Med Syst"},{"issue":"1","key":"1679_CR33","doi-asserted-by":"crossref","first-page":"28","DOI":"10.1006\/jbin.2001.1004","volume":"34","author":"S Dreiseitl","year":"2001","unstructured":"S. Dreiseitl, L. Ohno-Machado, H. Kittler, S. Vinterbo, H. Billhardt, and M. Binder, \u201cA comparison of machine learning methods for the diagnosis of pigmented skin lesions,\u201d Journal of biomedical informatics, vol. 34, no. 1, pp. 28\u201336, 2001.","journal-title":"Journal of biomedical informatics"},{"issue":"3","key":"1679_CR34","doi-asserted-by":"crossref","first-page":"167","DOI":"10.1016\/S0169-2607(99)00003-6","volume":"59","author":"J Sanders","year":"1999","unstructured":"J. Sanders, B. Goldstein, D. Leotta, and K. Richards, \u201cImage processing techniques for quantitative analysis of skin structures,\u201d Computer methods and programs in biomedicine, vol. 59, no. 3, pp. 167\u2013180, 1999.","journal-title":"Computer methods and programs in biomedicine"},{"issue":"1","key":"1679_CR35","doi-asserted-by":"crossref","first-page":"29","DOI":"10.1177\/030089169808400106","volume":"84","author":"S Tomatis","year":"1998","unstructured":"S. Tomatis, A. Bono, C. Bartoli, G. Tragni, B. Farina, and R. Marchesini, \u201cImage analysis in the RGB and HS colour planes for a computer-assisted diagnosis of cutaneous pigmented lesions,\u201d Tumori, vol. 84, no. 1, pp. 29\u201332, 1998.","journal-title":"Tumori"},{"issue":"4","key":"1679_CR36","doi-asserted-by":"crossref","first-page":"727","DOI":"10.1016\/0959-8049(95)00649-4","volume":"32","author":"A Bono","year":"1996","unstructured":"A. Bono et al., \u201cThe invisible colours of melanoma. A telespectrophotometric diagnostic approach on pigmented skin lesions,\u201d European Journal of Cancer, vol. 32, no. 4, pp. 727\u2013729, 1996.","journal-title":"European Journal of Cancer"},{"issue":"11","key":"1679_CR37","doi-asserted-by":"crossref","first-page":"1730","DOI":"10.1016\/S0959-8049(98)00210-X","volume":"34","author":"B Chwirot","year":"1998","unstructured":"B. Chwirot, S. Chwirot, J. Redzi\u0144ski, and Z. Michniewicz, \u201cDetection of melanomas by digital imaging of spectrally resolved ultraviolet light-induced autofluorescence of human skin,\u201d European Journal of Cancer, vol. 34, no. 11, pp. 1730\u20131734, 1998.","journal-title":"European Journal of Cancer"},{"doi-asserted-by":"crossref","unstructured":"I. Maglogiannis and E. Zafiropoulos, \u201cUtilizing support vector machines for the characterization of digital medical images,\u201d BMC Medical Informatics and Decision Making, vol. 4, no. 4, 2004.","key":"1679_CR38","DOI":"10.1186\/1472-6947-4-4"},{"issue":"1","key":"1679_CR39","doi-asserted-by":"crossref","first-page":"78","DOI":"10.1109\/42.552057","volume":"16","author":"GL Hansen","year":"1997","unstructured":"G. L. Hansen, E. M. Sparrow, J. Y. Kokate, K. J. Leland, and P. A. Iaizzo, \u201cWound status evaluation using color image processing,\u201d IEEE Transactions on Medical Imaging, vol. 16, no. 1, pp. 78\u201386, 1997.","journal-title":"IEEE Transactions on Medical Imaging"},{"unstructured":"Z. Zhang, R. H. Moss, and W. V. Stoecker, \u201cNeural networks skin tumor diagnostic system,\u201d 2003, vol. 1, pp. 191\u2013192.","key":"1679_CR40"},{"issue":"2","key":"1679_CR41","doi-asserted-by":"crossref","first-page":"69","DOI":"10.1016\/j.artmed.2012.08.002","volume":"56","author":"K Korotkov","year":"2012","unstructured":"K. Korotkov and R. Garcia, \u201cComputerized analysis of pigmented skin lesions: a review,\u201d Artificial intelligence in medicine, vol. 56, no. 2, pp. 69\u201390, 2012.","journal-title":"Artificial intelligence in medicine"},{"unstructured":"H. Motoyama, T. Tanaka, M. Tanaka, and H. Oka, \u201cFeature of malignant melanoma based on color information,\u201d 2004, vol. 1, pp. 230\u2013233.","key":"1679_CR42"},{"issue":"1","key":"1679_CR43","doi-asserted-by":"crossref","first-page":"39","DOI":"10.1109\/42.222664","volume":"12","author":"M Herbin","year":"1993","unstructured":"M. Herbin et al., \u201cAssessment of healing kinetics through true color image processing,\u201d IEEE Transactions on Medical Imaging, vol. 12, no. 1, pp. 39\u201343, 1993.","journal-title":"IEEE Transactions on Medical Imaging"},{"issue":"4","key":"1679_CR44","doi-asserted-by":"crossref","first-page":"201","DOI":"10.1007\/BF00735581","volume":"75","author":"W Lohmann","year":"1988","unstructured":"W. Lohmann and E. Paul, \u201cIn situ detection of melanomas by fluorescence measurements,\u201d Naturwissenschaften, vol. 75, no. 4, pp. 201\u2013202, 1988.","journal-title":"Naturwissenschaften"},{"issue":"3","key":"1679_CR45","doi-asserted-by":"crossref","first-page":"417","DOI":"10.1016\/j.jaad.2006.08.033","volume":"56","author":"JC Boldrick","year":"2007","unstructured":"J. C. Boldrick, C. J. Layton, J. Nguyen, and S. M. Swetter, \u201cEvaluation of digital dermoscopy in a pigmented lesion clinic: clinician versus computer assessment of malignancy risk,\u201d Journal of the American Academy of Dermatology, vol. 56, no. 3, pp. 417\u2013421, 2007.","journal-title":"Journal of the American Academy of Dermatology"},{"doi-asserted-by":"crossref","unstructured":"E. Lefevre, O. Colot, P. Vannoorenberghe, and D. de Brucq, \u201cKnowledge modeling methods in the framework of evidence theory: an experimental comparison for melanoma detection,\u201d 2000, vol. 4, pp. 2806\u20132811.","key":"1679_CR46","DOI":"10.1109\/ICSMC.2000.884422"},{"issue":"5","key":"1679_CR47","doi-asserted-by":"crossref","first-page":"387","DOI":"10.1016\/S0895-6111(03)00030-2","volume":"27","author":"RJ Stanley","year":"2003","unstructured":"R. J. Stanley, R. H. Moss, W. Van Stoecker, and C. Aggarwal, \u201cA fuzzy-based histogram analysis technique for skin lesion discrimination in dermatology clinical images,\u201d Computerized Medical Imaging and Graphics, vol. 27, no. 5, pp. 387\u2013396, 2003.","journal-title":"Computerized Medical Imaging and Graphics"},{"issue":"4","key":"1679_CR48","doi-asserted-by":"crossref","first-page":"62","DOI":"10.1109\/51.603650","volume":"16","author":"SE Umbaugh","year":"1997","unstructured":"S. E. Umbaugh, Y.-S. Wei, and M. Zuke, \u201cFeature extraction in image analysis. A program for facilitating data reduction in medical image classification,\u201d IEEE engineering in medicine and biology magazine, vol. 16, no. 4, pp. 62\u201373, 1997.","journal-title":"IEEE engineering in medicine and biology magazine"},{"issue":"1","key":"1679_CR49","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1007\/s10916-018-1112-5","volume":"43","author":"M Monisha","year":"2018","unstructured":"M. Monisha, A. Suresh, and M. R. Rashmi, \u201cArtificial Intelligence Based Skin Classification Using GMM,\u201d J Med Syst, vol. 43, no. 1, p. 3, 2018, https:\/\/doi.org\/10.1007\/s10916-018-1112-5.","journal-title":"J Med Syst"},{"issue":"3","key":"1679_CR50","doi-asserted-by":"crossref","first-page":"233","DOI":"10.1109\/42.918473","volume":"20","author":"H Ganster","year":"2001","unstructured":"H. Ganster, P. Pinz, R. Rohrer, E. Wildling, M. Binder, and H. Kittler, \u201cAutomated melanoma recognition,\u201d IEEE transactions on medical imaging, vol. 20, no. 3, pp. 233\u2013239, 2001.","journal-title":"IEEE transactions on medical imaging"},{"issue":"8","key":"1679_CR51","doi-asserted-by":"crossref","first-page":"959","DOI":"10.1109\/TMI.2003.815901","volume":"22","author":"C Grana","year":"2003","unstructured":"C. Grana, G. Pellacani, R. Cucchiara, and S. Seidenari, \u201cA new algorithm for border description of polarized light surface microscopic images of pigmented skin lesions,\u201d IEEE Transactions on Medical Imaging, vol. 22, no. 8, pp. 959\u2013964, 2003.","journal-title":"IEEE Transactions on Medical Imaging"},{"issue":"6","key":"1679_CR52","doi-asserted-by":"crossref","first-page":"576","DOI":"10.1002\/ijc.10620","volume":"101","author":"P Rubegni","year":"2002","unstructured":"P. Rubegni et al., \u201cAutomated diagnosis of pigmented skin lesions,\u201d International Journal of Cancer, vol. 101, no. 6, pp. 576\u2013580, 2002.","journal-title":"International Journal of Cancer"},{"issue":"9","key":"1679_CR53","doi-asserted-by":"crossref","first-page":"837","DOI":"10.1109\/10.312091","volume":"41","author":"F Ercal","year":"1994","unstructured":"F. Ercal, A. Chawla, W. V. Stoecker, H.-C. Lee, and R. H. Moss, \u201cNeural network diagnosis of malignant melanoma from color images,\u201d IEEE Transactions on biomedical engineering, vol. 41, no. 9, pp. 837\u2013845, 1994.","journal-title":"IEEE Transactions on biomedical engineering"},{"issue":"16","key":"1679_CR54","doi-asserted-by":"crossref","first-page":"2626","DOI":"10.1093\/bioinformatics\/bth294","volume":"20","author":"GR Lanckriet","year":"2004","unstructured":"G. R. Lanckriet, T. De Bie, N. Cristianini, M. I. Jordan, and W. S. Noble, \u201cA statistical framework for genomic data fusion,\u201d Bioinformatics, vol. 20, no. 16, pp. 2626\u20132635, 2004.","journal-title":"Bioinformatics"},{"doi-asserted-by":"crossref","unstructured":"J. Ye et al., \u201cHeterogeneous data fusion for alzheimer\u2019s disease study,\u201d 2008, pp. 1025\u20131033.","key":"1679_CR55","DOI":"10.1145\/1401890.1402012"},{"issue":"22","key":"1679_CR56","doi-asserted-by":"crossref","first-page":"6987","DOI":"10.1158\/1078-0432.CCR-09-1777","volume":"15","author":"M Kashani-Sabet","year":"2009","unstructured":"M. Kashani-Sabet et al., \u201cA multimarker prognostic assay for primary cutaneous melanoma,\u201d Clinical Cancer Research, vol. 15, no. 22, pp. 6987\u20136992, 2009.","journal-title":"Clinical Cancer Research"},{"issue":"2","key":"1679_CR57","doi-asserted-by":"crossref","first-page":"509","DOI":"10.1038\/jid.2012.283","volume":"133","author":"GJ Mann","year":"2013","unstructured":"G. J. Mann et al., \u201cBRAF mutation, NRAS mutation, and the absence of an immune-related expressed gene profile predict poor outcome in patients with stage III melanoma,\u201d Journal of Investigative Dermatology, vol. 133, no. 2, pp. 509\u2013517, 2013.","journal-title":"Journal of Investigative Dermatology"},{"doi-asserted-by":"crossref","unstructured":"B. E. G. Rothberg, M. B. Bracken, and D. L. Rimm, \u201cTissue biomarkers for prognosis in cutaneous melanoma: a systematic review and meta-analysis,\u201d Journal of the national cancer institute, 2009.","key":"1679_CR58","DOI":"10.1093\/jnci\/djp038"},{"issue":"11","key":"1679_CR59","doi-asserted-by":"publisher","first-page":"130","DOI":"10.1007\/s12032-016-0840-y","volume":"33","author":"Z Xu","year":"2016","unstructured":"Z. Xu, Y. Zhou, Y. Cao, T. L. Dinh, J. Wan, and M. Zhao, \u201cIdentification of candidate biomarkers and analysis of prognostic values in ovarian cancer by integrated bioinformatics analysis,\u201d Medical oncology (Northwood, London, England), vol. 33, no. 11, p. 130, 2016, https:\/\/doi.org\/10.1007\/s12032-016-0840-y.","journal-title":"Medical oncology (Northwood, London, England)"},{"issue":"12","key":"1679_CR60","doi-asserted-by":"publisher","first-page":"e542","DOI":"10.1016\/s1470-2045(16)30406-5","volume":"17","author":"GT Gibney","year":"2016","unstructured":"G. T. Gibney, L. M. Weiner, and M. B. Atkins, \u201cPredictive biomarkers for checkpoint inhibitor-based immunotherapy,\u201d The Lancet. Oncology, vol. 17, no. 12, pp. e542\u2013e551, 2016, https:\/\/doi.org\/10.1016\/s1470-2045(16)30406-5.","journal-title":"The Lancet. Oncology"},{"key":"1679_CR61","doi-asserted-by":"publisher","first-page":"145243","DOI":"10.1155\/2014\/145243","volume":"2014","author":"K Moutselos","year":"2014","unstructured":"K. Moutselos, I. Maglogiannis, and A. Chatziioannou, \u201cIntegration of high-volume molecular and imaging data for composite biomarker discovery in the study of melanoma,\u201d BioMed research international, vol. 2014, p. 145243, 2014, https:\/\/doi.org\/10.1155\/2014\/145243.","journal-title":"BioMed research international"},{"doi-asserted-by":"crossref","unstructured":"I. Valavanis, I. Maglogiannis, and A. Chatziioannou, \u201cExploring robust diagnostic signatures for cutaneous melanoma utilizing genetic and imaging data,\u201d IEEE journal of biomedical and health informatics, pp. 190\u2013198, 2015.","key":"1679_CR62","DOI":"10.1109\/JBHI.2014.2336617"},{"unstructured":"epsos.","key":"1679_CR63"},{"doi-asserted-by":"crossref","unstructured":"M. Maragoudakis and I. Maglogiannis, \u201cSkin lesion diagnosis from images using novel ensemble classification techniques,\u201d 2010, pp. 1\u20135.","key":"1679_CR64","DOI":"10.1109\/ITAB.2010.5687620"},{"issue":"1","key":"1679_CR65","doi-asserted-by":"crossref","first-page":"86","DOI":"10.1109\/TITB.2004.837859","volume":"9","author":"I Maglogiannis","year":"2005","unstructured":"I. Maglogiannis, S. Pavlopoulos, and D. Koutsouris, \u201cAn integrated computer supported acquisition, handling, and characterization system for pigmented skin lesions in dermatological images,\u201d IEEE Transactions on Information Technology in Biomedicine, vol. 9, no. 1, pp. 86\u201398, 2005.","journal-title":"IEEE Transactions on Information Technology in Biomedicine"},{"doi-asserted-by":"crossref","unstructured":"G. Kontogianni, O. Papadodima, I. Maglogiannis, K. Frangia-Tsivou, and A. Chatziioannou, \u201cIntegrative Bioinformatic Analysis of a Greek Epidemiological Cohort Provides Insight into the Pathogenesis of Primary Cutaneous Melanoma,\u201d 2016.","key":"1679_CR66","DOI":"10.1007\/978-3-319-44944-9_4"},{"issue":"4","key":"1679_CR67","doi-asserted-by":"publisher","first-page":"96","DOI":"10.3390\/cancers10040096","volume":"10","author":"G Kontogianni","year":"2018","unstructured":"G. Kontogianni, G. Piroti, I. Maglogiannis, A. Chatziioannou, and O. Papadodima, \u201cDissecting the Mutational Landscape of Cutaneous Melanoma: An Omic Analysis Based on Patients from Greece,\u201d Cancers, vol. 10, no. 4, p. 96, 2018, https:\/\/doi.org\/10.3390\/cancers10040096.","journal-title":"Cancers"},{"doi-asserted-by":"crossref","unstructured":"E. Cerami et al., \u201cThe cBio cancer genomics portal: an open platform for exploring multidimensional cancer genomics data,\u201d 2012.","key":"1679_CR68","DOI":"10.1158\/2159-8290.CD-12-0095"},{"issue":"269","key":"1679_CR69","doi-asserted-by":"publisher","first-page":"pl1","DOI":"10.1126\/scisignal.2004088","volume":"6","author":"J Gao","year":"2013","unstructured":"J. Gao et al., \u201cIntegrative analysis of complex cancer genomics and clinical profiles using the cBioPortal,\u201d Science signaling, vol. 6, no. 269, p. pl1, 2013, https:\/\/doi.org\/10.1126\/scisignal.2004088.","journal-title":"Science signaling"},{"issue":"4","key":"1679_CR70","doi-asserted-by":"crossref","first-page":"905","DOI":"10.1016\/j.jid.2016.11.017","volume":"137","author":"RD Melamed","year":"2017","unstructured":"R. D. Melamed et al., \u201cGenomic characterization of dysplastic nevi unveils implications for diagnosis of melanoma,\u201d Journal of Investigative Dermatology, vol. 137, no. 4, pp. 905\u2013909, 2017.","journal-title":"Journal of Investigative Dermatology"},{"doi-asserted-by":"crossref","unstructured":"I. A. Adzhubei et al., \u201cA method and server for predicting damaging missense mutations,\u201d in Nat Methods, vol. 7, United States, 2010, pp. 248\u20139.","key":"1679_CR71","DOI":"10.1038\/nmeth0410-248"},{"issue":"2","key":"1679_CR72","doi-asserted-by":"crossref","first-page":"30","DOI":"10.4018\/IJMSTR.2016040103","volume":"4","author":"T Koutsandreas","year":"2016","unstructured":"T. Koutsandreas, I. Binenbaum, E. Pilalis, I. Valavanis, O. Papadodima, and A. Chatziioannou, \u201cAnalyzing and visualizing genomic complexity for the derivation of the emergent molecular networks,\u201d International Journal of Monitoring and Surveillance Technologies Research (IJMSTR), vol. 4, no. 2, pp. 30\u201349, 2016.","journal-title":"International Journal of Monitoring and Surveillance Technologies Research (IJMSTR)"},{"issue":"1","key":"1679_CR73","doi-asserted-by":"publisher","first-page":"25","DOI":"10.1038\/75556","volume":"25","author":"M Ashburner","year":"2000","unstructured":"M. Ashburner et al., \u201cGene ontology: tool for the unification of biology. The Gene Ontology Consortium,\u201d Nature genetics, vol. 25, no. 1, pp. 25\u20139, 2000, https:\/\/doi.org\/10.1038\/75556.","journal-title":"Nature genetics"},{"issue":"D1","key":"1679_CR74","doi-asserted-by":"publisher","first-page":"D330","DOI":"10.1093\/nar\/gky1055","volume":"47","author":"The Gene Ontology Consortium","year":"2019","unstructured":"The Gene Ontology Consortium, \u201cThe Gene Ontology Resource: 20 years and still GOing strong,\u201d Nucleic Acids Res., vol. 47, no. D1, pp. D330\u2013D338, 2019, https:\/\/doi.org\/10.1093\/nar\/gky1055.","journal-title":"Nucleic Acids Res."},{"issue":"D1","key":"1679_CR75","doi-asserted-by":"publisher","first-page":"D649","DOI":"10.1093\/nar\/gkx1132","volume":"46","author":"A Fabregat","year":"2018","unstructured":"A. Fabregat et al., \u201cThe Reactome Pathway Knowledgebase,\u201d Nucleic Acids Res., vol. 46, no. D1, pp. D649\u2013D655, 2018, https:\/\/doi.org\/10.1093\/nar\/gkx1132.","journal-title":"Nucleic Acids Res."},{"key":"1679_CR76","doi-asserted-by":"crossref","first-page":"321","DOI":"10.1613\/jair.953","volume":"16","author":"NV Chawla","year":"2002","unstructured":"N. V. Chawla, K. W. Bowyer, L. O. Hall, and W. P. Kegelmeyer, \u201cSMOTE: synthetic minority over-sampling technique,\u201d Journal of artificial intelligence research, vol. 16, pp. 321\u2013357, 2002.","journal-title":"Journal of artificial intelligence research"},{"issue":"6","key":"1679_CR77","doi-asserted-by":"publisher","first-page":"323","DOI":"10.1016\/j.ygeno.2012.04.003","volume":"99","author":"X Chen","year":"2012","unstructured":"X. Chen and H. Ishwaran, \u201cRandom forests for genomic data analysis,\u201d Genomics, vol. 99, no. 6, pp. 323\u20139, 2012, https:\/\/doi.org\/10.1016\/j.ygeno.2012.04.003.","journal-title":"Genomics"},{"unstructured":"R. Development (2011) \u201cCore TeamR: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing,\u201d ISBN 3-900051-07-0. Available: h ttp:\/\/www. R-project. org.","key":"1679_CR78"},{"unstructured":"M. Kuhn, \u201cCaret: classification and regression training,\u201d Astrophysics Source Code Library, 2015.","key":"1679_CR79"},{"doi-asserted-by":"crossref","unstructured":"L. Torgo, Data mining with R: learning with case studies. CRC press, 2016.","key":"1679_CR80","DOI":"10.1201\/9781315399102"},{"issue":"1","key":"1679_CR81","doi-asserted-by":"crossref","first-page":"77","DOI":"10.1186\/1471-2105-12-77","volume":"12","author":"X Robin","year":"2011","unstructured":"X. Robin et al., \u201cpROC: an open-source package for R and S+ to analyze and compare ROC curves,\u201d BMC bioinformatics, vol. 12, no. 1, p. 77, 2011.","journal-title":"BMC bioinformatics"},{"issue":"2","key":"1679_CR82","first-page":"627","volume":"4","author":"K Hajian-Tilaki","year":"2013","unstructured":"K. Hajian-Tilaki, \u201cReceiver Operating Characteristic (ROC) Curve Analysis for Medical Diagnostic Test Evaluation,\u201d Caspian journal of internal medicine, vol. 4, no. 2, pp. 627\u201335, Spring 2013.","journal-title":"Caspian journal of internal medicine"},{"unstructured":"Brooke, J., \u201cSUS \u2013 A Quick and Dirty Usability Scale,\u201d in Usability Evaluation in Industry, vol. 194, 1996, pp. 4\u20137.","key":"1679_CR83"},{"issue":"2","key":"1679_CR84","first-page":"29","volume":"8","author":"J Brooke","year":"2013","unstructured":"Brooke, J., \u201cSUS: a retrospective,\u201d Journal of usability studies, vol. 8, no. 2, pp. 29\u201340, 2013.","journal-title":"Journal of usability studies"}],"container-title":["Journal of Medical Systems"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10916-020-01679-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s10916-020-01679-3\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10916-020-01679-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,8,21]],"date-time":"2024-08-21T23:28:18Z","timestamp":1724282898000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s10916-020-01679-3"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,1]]},"references-count":84,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2021,1]]}},"alternative-id":["1679"],"URL":"https:\/\/doi.org\/10.1007\/s10916-020-01679-3","relation":{},"ISSN":["0148-5598","1573-689X"],"issn-type":[{"type":"print","value":"0148-5598"},{"type":"electronic","value":"1573-689X"}],"subject":[],"published":{"date-parts":[[2021,1]]},"assertion":[{"value":"11 April 2019","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"23 November 2020","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"6 January 2021","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Compliance with ethical standards"}},{"value":"The authors declare that they have no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}},{"value":"Since all datasets included in this article were either from public databases or from previously published studies additional approval by an ethics committee was unnecessary. All human samples were acquired in the context of a prior project entitled 12CHN-204 PROMISE (Bilateral Greece-China Research Program of the Hellenic General Secretariat of Research and Technology and the Chinese Ministry of Research and Technology entitled \u201cPersonalization of melanoma therapeutic management through the fusion of systems biology and intelligent data mining methodologies-PROMISE\u201d, sponsored by the Program \u201cCompetitiveness and Entrepreneurship\u201d, Priority Health of the Peripheral Entrepreneurial Program of Attiki), under the strict conformity to the rules of the call. All procedures performed in studies involving human participants were in accordance with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.\u201d","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethical approval"}}],"article-number":"10"}}