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01.01.2021 | Transactional Processing Systems

An Integrated Platform for Skin Cancer Heterogenous and Multilayered Data Management

verfasst von: Ilias Maglogiannis, Georgia Kontogianni, Olga Papadodima, Haralampos Karanikas, Antonis Billiris, Aristotelis Chatziioannou

Erschienen in: Journal of Medical Systems | Ausgabe 1/2021

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Abstract

Electronic health record (EHR) systems improve health care services by allowing the combination of health data with clinical decision support features and clinical image analyses. This study presents a modular and distributed platform that is able to integrate and accommodate heterogeneous, multidimensional (omics, histological images and clinical) data for the multi-angled portrayal and management of skin cancer patients. The proposed design offers a layered analytical framework as an expansion of current EHR systems, which can integrate high-volume molecular -omics data, imaging data, as well as relevant clinical observations. We present a case study in the field of dermatology, where we attempt to combine the multilayered information for the early detection and characterization of melanoma. The specific architecture aspires to lower the barrier for the introduction of personalized therapeutic approaches, towards precision medicine. The paper describes the technical issues of implementation, along with an initial evaluation of the system and discussion.
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Literatur
1.
Zurück zum Zitat P. J. O’Connor, J. R. Desai, J. C. Butler, E. O. Kharbanda, and J. M. Sperl-Hillen, “Current status and future prospects for electronic point-of-care clinical decision support in diabetes care,” Current diabetes reports, vol. 13, no. 2, pp. 172–176, 2013.PubMedPubMedCentral P. J. O’Connor, J. R. Desai, J. C. Butler, E. O. Kharbanda, and J. M. Sperl-Hillen, “Current status and future prospects for electronic point-of-care clinical decision support in diabetes care,” Current diabetes reports, vol. 13, no. 2, pp. 172–176, 2013.PubMedPubMedCentral
2.
Zurück zum Zitat E. De Vries, V. De Poll-Franse, W. Louwman, F. De Gruijl, and J. Coebergh, “Predictions of skin cancer incidence in the Netherlands up to 2015,” British Journal of Dermatology, vol. 152, no. 3, pp. 481–488, 2005. E. De Vries, V. De Poll-Franse, W. Louwman, F. De Gruijl, and J. Coebergh, “Predictions of skin cancer incidence in the Netherlands up to 2015,” British Journal of Dermatology, vol. 152, no. 3, pp. 481–488, 2005.
3.
Zurück zum Zitat G. P. Guy et al., “Vital signs: melanoma incidence and mortality trends and projections - United States, 1982–2030,” MMWR Morb. Mortal. Wkly. Rep., vol. 64, no. 21, pp. 591–596, 2015.PubMedPubMedCentral G. P. Guy et al., “Vital signs: melanoma incidence and mortality trends and projections - United States, 1982–2030,” MMWR Morb. Mortal. Wkly. Rep., vol. 64, no. 21, pp. 591–596, 2015.PubMedPubMedCentral
4.
Zurück zum Zitat A. M. Bailey et al., “Implementation of biomarker-driven cancer therapy: existing tools and remaining gaps,” Discovery medicine, vol. 17, no. 92, p. 101, 2014.PubMedPubMedCentral A. M. Bailey et al., “Implementation of biomarker-driven cancer therapy: existing tools and remaining gaps,” Discovery medicine, vol. 17, no. 92, p. 101, 2014.PubMedPubMedCentral
6.
Zurück zum Zitat X. Wei et al., “Exome sequencing identifies GRIN2A as frequently mutated in melanoma,” Nature genetics, vol. 43, no. 5, pp. 442–446, 2011.PubMedPubMedCentral X. Wei et al., “Exome sequencing identifies GRIN2A as frequently mutated in melanoma,” Nature genetics, vol. 43, no. 5, pp. 442–446, 2011.PubMedPubMedCentral
10.
Zurück zum Zitat C. Castaneda et al., “Clinical decision support systems for improving diagnostic accuracy and achieving precision medicine,” Journal of clinical bioinformatics, vol. 5, no. 1, p. 4, 2015.PubMedPubMedCentral C. Castaneda et al., “Clinical decision support systems for improving diagnostic accuracy and achieving precision medicine,” Journal of clinical bioinformatics, vol. 5, no. 1, p. 4, 2015.PubMedPubMedCentral
11.
Zurück zum Zitat L. Kuhn et al., “Planning 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,” The Journal of the American Board of Family Medicine, vol. 28, no. 3, pp. 382–393, 2015.PubMed L. Kuhn et al., “Planning 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,” The Journal of the American Board of Family Medicine, vol. 28, no. 3, pp. 382–393, 2015.PubMed
12.
Zurück zum Zitat W. Ceusters and B. Smith, “Semantic Interoperability in Healthcare State of the Art in the US,” New York State Center of Excellence in Bioinformatics and Life Sciences Ontology Research Group, pp. 1–33, 2010. W. Ceusters and B. Smith, “Semantic Interoperability in Healthcare State of the Art in the US,” New York State Center of Excellence in Bioinformatics and Life Sciences Ontology Research Group, pp. 1–33, 2010.
13.
Zurück zum Zitat C. Hahn, S. Jacobi, and D. Raber, “Enhancing the interoperability between multiagent systems and service-oriented architectures through a model-driven approach,” 2010, vol. 2, pp. 415–422. C. Hahn, S. Jacobi, and D. Raber, “Enhancing the interoperability between multiagent systems and service-oriented architectures through a model-driven approach,” 2010, vol. 2, pp. 415–422.
14.
Zurück zum Zitat World Wide Web Consortium, 2012. 2012. World Wide Web Consortium, 2012. 2012.
15.
Zurück zum Zitat J. Bacon and K. Moody, “Toward open, secure, widely distributed services,” Communications of the ACM, vol. 45, no. 6, pp. 59–64, 2002. J. Bacon and K. Moody, “Toward open, secure, widely distributed services,” Communications of the ACM, vol. 45, no. 6, pp. 59–64, 2002.
16.
Zurück zum Zitat H. Catalyst, Late-Binding Data Warehouse, Health Catalyst.. H. Catalyst, Late-Binding Data Warehouse, Health Catalyst..
17.
Zurück zum Zitat Diving in: Navigating a data lake for predictive care Patient Data Intelligence fo Next-Generation Care Delivery. Diving in: Navigating a data lake for predictive care Patient Data Intelligence fo Next-Generation Care Delivery.
19.
Zurück zum Zitat A. T. Janke, D. L. Overbeek, K. E. Kocher, and P. D. Levy, “Exploring the potential of predictive analytics and big data in emergency care,” Annals of emergency medicine, vol. 67, no. 2, pp. 227–236, 2016.PubMed A. T. Janke, D. L. Overbeek, K. E. Kocher, and P. D. Levy, “Exploring the potential of predictive analytics and big data in emergency care,” Annals of emergency medicine, vol. 67, no. 2, pp. 227–236, 2016.PubMed
20.
Zurück zum Zitat A. Holzinger and I. Jurisica, “Knowledge discovery and data mining in biomedical informatics: The future is in integrative, interactive machine learning solutions,” in Interactive knowledge discovery and data mining in biomedical informatics, Springer, 2014, pp. 1–18. A. Holzinger and I. Jurisica, “Knowledge discovery and data mining in biomedical informatics: The future is in integrative, interactive machine learning solutions,” in Interactive knowledge discovery and data mining in biomedical informatics, Springer, 2014, pp. 1–18.
22.
Zurück zum Zitat F. Wang, L. S. Docherty, K. J. Turner, M. Kolberg, and E. H. Magill, “Services and policies for care at home,” 2006, pp. 1–10. F. Wang, L. S. Docherty, K. J. Turner, M. Kolberg, and E. H. Magill, “Services and policies for care at home,” 2006, pp. 1–10.
23.
Zurück zum Zitat N. T. Issa, S. W. Byers, and S. Dakshanamurthy, “Big data: the next frontier for innovation in therapeutics and healthcare,” Expert review of clinical pharmacology, vol. 7, no. 3, pp. 293–298, 2014.PubMedPubMedCentral N. T. Issa, S. W. Byers, and S. Dakshanamurthy, “Big data: the next frontier for innovation in therapeutics and healthcare,” Expert review of clinical pharmacology, vol. 7, no. 3, pp. 293–298, 2014.PubMedPubMedCentral
24.
Zurück zum Zitat T. Goudas and I. Maglogiannis, “An advanced image analysis tool for the quantification and characterization of breast cancer in microscopy images,” Journal of medical systems, vol. 39, no. 3, p. 31, 2015.PubMed T. Goudas and I. Maglogiannis, “An advanced image analysis tool for the quantification and characterization of breast cancer in microscopy images,” Journal of medical systems, vol. 39, no. 3, p. 31, 2015.PubMed
25.
Zurück zum Zitat G. Argenziano, G. Fabbrocini, P. Carli, V. De Giorgi, E. Sammarco, and M. Delfino, “Epiluminescence 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,” Archives of dermatology, vol. 134, no. 12, pp. 1563–70, 1998.PubMed G. Argenziano, G. Fabbrocini, P. Carli, V. De Giorgi, E. Sammarco, and M. Delfino, “Epiluminescence 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,” Archives of dermatology, vol. 134, no. 12, pp. 1563–70, 1998.PubMed
26.
Zurück zum Zitat G. Betta, G. Di Leo, G. Fabbrocini, A. Paolillo, and M. Scalvenzi, “Automated Application of the ‘7-point checklist’ Diagnosis Method for Skin Lesions: Estimation of Chromatic and Shape Parameters,” 2005, vol. 3, pp. 1818–1822. G. Betta, G. Di Leo, G. Fabbrocini, A. Paolillo, and M. Scalvenzi, “Automated Application of the ‘7-point checklist’ Diagnosis Method for Skin Lesions: Estimation of Chromatic and Shape Parameters,” 2005, vol. 3, pp. 1818–1822.
27.
Zurück zum Zitat M. Ogorzałek, L. Nowak, G. Surowka, and A. Alekseenko, “Melanoma in the clinic—diagnosis, management and complications of malignancy,” Modern Techniques for Computer-Aided Melanoma Diagnosis, 2011. M. Ogorzałek, L. Nowak, G. Surowka, and A. Alekseenko, “Melanoma in the clinic—diagnosis, management and complications of malignancy,” Modern Techniques for Computer-Aided Melanoma Diagnosis, 2011.
29.
Zurück zum Zitat I. Maglogiannis and C. N. Doukas, “Overview of advanced computer vision systems for skin lesions characterization,” IEEE transactions on information technology in biomedicine, vol. 13, no. 5, pp. 721–733, 2009.PubMed I. Maglogiannis and C. N. Doukas, “Overview of advanced computer vision systems for skin lesions characterization,” IEEE transactions on information technology in biomedicine, vol. 13, no. 5, pp. 721–733, 2009.PubMed
30.
Zurück zum Zitat A. G. Manousaki et al., “A simple digital image processing system to aid in melanoma diagnosis in an everyday melanocytic skin lesion unit. A preliminary report,” International journal of dermatology, vol. 45, no. 4, pp. 402–410, 2006.PubMed A. G. Manousaki et al., “A simple digital image processing system to aid in melanoma diagnosis in an everyday melanocytic skin lesion unit. A preliminary report,” International journal of dermatology, vol. 45, no. 4, pp. 402–410, 2006.PubMed
31.
Zurück zum Zitat S. E. Umbaugh, R. H. Moss, and W. V. Stoecker, “Applying artificial intelligence to the identification of variegated coloring in skin tumors,” IEEE engineering in medicine and biology magazine, vol. 10, no. 4, pp. 57–62, 1991.PubMed S. E. Umbaugh, R. H. Moss, and W. V. Stoecker, “Applying artificial intelligence to the identification of variegated coloring in skin tumors,” IEEE engineering in medicine and biology magazine, vol. 10, no. 4, pp. 57–62, 1991.PubMed
33.
Zurück zum Zitat S. Dreiseitl, L. Ohno-Machado, H. Kittler, S. Vinterbo, H. Billhardt, and M. Binder, “A comparison of machine learning methods for the diagnosis of pigmented skin lesions,” Journal of biomedical informatics, vol. 34, no. 1, pp. 28–36, 2001.PubMed S. Dreiseitl, L. Ohno-Machado, H. Kittler, S. Vinterbo, H. Billhardt, and M. Binder, “A comparison of machine learning methods for the diagnosis of pigmented skin lesions,” Journal of biomedical informatics, vol. 34, no. 1, pp. 28–36, 2001.PubMed
34.
Zurück zum Zitat J. Sanders, B. Goldstein, D. Leotta, and K. Richards, “Image processing techniques for quantitative analysis of skin structures,” Computer methods and programs in biomedicine, vol. 59, no. 3, pp. 167–180, 1999.PubMed J. Sanders, B. Goldstein, D. Leotta, and K. Richards, “Image processing techniques for quantitative analysis of skin structures,” Computer methods and programs in biomedicine, vol. 59, no. 3, pp. 167–180, 1999.PubMed
35.
Zurück zum Zitat S. Tomatis, A. Bono, C. Bartoli, G. Tragni, B. Farina, and R. Marchesini, “Image analysis in the RGB and HS colour planes for a computer-assisted diagnosis of cutaneous pigmented lesions,” Tumori, vol. 84, no. 1, pp. 29–32, 1998.PubMed S. Tomatis, A. Bono, C. Bartoli, G. Tragni, B. Farina, and R. Marchesini, “Image analysis in the RGB and HS colour planes for a computer-assisted diagnosis of cutaneous pigmented lesions,” Tumori, vol. 84, no. 1, pp. 29–32, 1998.PubMed
36.
Zurück zum Zitat A. Bono et al., “The invisible colours of melanoma. A telespectrophotometric diagnostic approach on pigmented skin lesions,” European Journal of Cancer, vol. 32, no. 4, pp. 727–729, 1996. A. Bono et al., “The invisible colours of melanoma. A telespectrophotometric diagnostic approach on pigmented skin lesions,” European Journal of Cancer, vol. 32, no. 4, pp. 727–729, 1996.
37.
Zurück zum Zitat B. Chwirot, S. Chwirot, J. Redziński, and Z. Michniewicz, “Detection of melanomas by digital imaging of spectrally resolved ultraviolet light-induced autofluorescence of human skin,” European Journal of Cancer, vol. 34, no. 11, pp. 1730–1734, 1998.PubMed B. Chwirot, S. Chwirot, J. Redziński, and Z. Michniewicz, “Detection of melanomas by digital imaging of spectrally resolved ultraviolet light-induced autofluorescence of human skin,” European Journal of Cancer, vol. 34, no. 11, pp. 1730–1734, 1998.PubMed
38.
Zurück zum Zitat I. Maglogiannis and E. Zafiropoulos, “Utilizing support vector machines for the characterization of digital medical images,” BMC Medical Informatics and Decision Making, vol. 4, no. 4, 2004. I. Maglogiannis and E. Zafiropoulos, “Utilizing support vector machines for the characterization of digital medical images,” BMC Medical Informatics and Decision Making, vol. 4, no. 4, 2004.
39.
Zurück zum Zitat G. L. Hansen, E. M. Sparrow, J. Y. Kokate, K. J. Leland, and P. A. Iaizzo, “Wound status evaluation using color image processing,” IEEE Transactions on Medical Imaging, vol. 16, no. 1, pp. 78–86, 1997.PubMed G. L. Hansen, E. M. Sparrow, J. Y. Kokate, K. J. Leland, and P. A. Iaizzo, “Wound status evaluation using color image processing,” IEEE Transactions on Medical Imaging, vol. 16, no. 1, pp. 78–86, 1997.PubMed
40.
Zurück zum Zitat Z. Zhang, R. H. Moss, and W. V. Stoecker, “Neural networks skin tumor diagnostic system,” 2003, vol. 1, pp. 191–192. Z. Zhang, R. H. Moss, and W. V. Stoecker, “Neural networks skin tumor diagnostic system,” 2003, vol. 1, pp. 191–192.
41.
Zurück zum Zitat K. Korotkov and R. Garcia, “Computerized analysis of pigmented skin lesions: a review,” Artificial intelligence in medicine, vol. 56, no. 2, pp. 69–90, 2012.PubMed K. Korotkov and R. Garcia, “Computerized analysis of pigmented skin lesions: a review,” Artificial intelligence in medicine, vol. 56, no. 2, pp. 69–90, 2012.PubMed
42.
Zurück zum Zitat H. Motoyama, T. Tanaka, M. Tanaka, and H. Oka, “Feature of malignant melanoma based on color information,” 2004, vol. 1, pp. 230–233. H. Motoyama, T. Tanaka, M. Tanaka, and H. Oka, “Feature of malignant melanoma based on color information,” 2004, vol. 1, pp. 230–233.
43.
Zurück zum Zitat M. Herbin et al., “Assessment of healing kinetics through true color image processing,” IEEE Transactions on Medical Imaging, vol. 12, no. 1, pp. 39–43, 1993.PubMed M. Herbin et al., “Assessment of healing kinetics through true color image processing,” IEEE Transactions on Medical Imaging, vol. 12, no. 1, pp. 39–43, 1993.PubMed
44.
Zurück zum Zitat W. Lohmann and E. Paul, “In situ detection of melanomas by fluorescence measurements,” Naturwissenschaften, vol. 75, no. 4, pp. 201–202, 1988.PubMed W. Lohmann and E. Paul, “In situ detection of melanomas by fluorescence measurements,” Naturwissenschaften, vol. 75, no. 4, pp. 201–202, 1988.PubMed
45.
Zurück zum Zitat J. C. Boldrick, C. J. Layton, J. Nguyen, and S. M. Swetter, “Evaluation of digital dermoscopy in a pigmented lesion clinic: clinician versus computer assessment of malignancy risk,” Journal of the American Academy of Dermatology, vol. 56, no. 3, pp. 417–421, 2007.PubMed J. C. Boldrick, C. J. Layton, J. Nguyen, and S. M. Swetter, “Evaluation of digital dermoscopy in a pigmented lesion clinic: clinician versus computer assessment of malignancy risk,” Journal of the American Academy of Dermatology, vol. 56, no. 3, pp. 417–421, 2007.PubMed
46.
Zurück zum Zitat E. Lefevre, O. Colot, P. Vannoorenberghe, and D. de Brucq, “Knowledge modeling methods in the framework of evidence theory: an experimental comparison for melanoma detection,” 2000, vol. 4, pp. 2806–2811. E. Lefevre, O. Colot, P. Vannoorenberghe, and D. de Brucq, “Knowledge modeling methods in the framework of evidence theory: an experimental comparison for melanoma detection,” 2000, vol. 4, pp. 2806–2811.
47.
Zurück zum Zitat R. J. Stanley, R. H. Moss, W. Van Stoecker, and C. Aggarwal, “A fuzzy-based histogram analysis technique for skin lesion discrimination in dermatology clinical images,” Computerized Medical Imaging and Graphics, vol. 27, no. 5, pp. 387–396, 2003.PubMedPubMedCentral R. J. Stanley, R. H. Moss, W. Van Stoecker, and C. Aggarwal, “A fuzzy-based histogram analysis technique for skin lesion discrimination in dermatology clinical images,” Computerized Medical Imaging and Graphics, vol. 27, no. 5, pp. 387–396, 2003.PubMedPubMedCentral
48.
Zurück zum Zitat S. E. Umbaugh, Y.-S. Wei, and M. Zuke, “Feature extraction in image analysis. A program for facilitating data reduction in medical image classification,” IEEE engineering in medicine and biology magazine, vol. 16, no. 4, pp. 62–73, 1997.PubMed S. E. Umbaugh, Y.-S. Wei, and M. Zuke, “Feature extraction in image analysis. A program for facilitating data reduction in medical image classification,” IEEE engineering in medicine and biology magazine, vol. 16, no. 4, pp. 62–73, 1997.PubMed
50.
Zurück zum Zitat H. Ganster, P. Pinz, R. Rohrer, E. Wildling, M. Binder, and H. Kittler, “Automated melanoma recognition,” IEEE transactions on medical imaging, vol. 20, no. 3, pp. 233–239, 2001.PubMed H. Ganster, P. Pinz, R. Rohrer, E. Wildling, M. Binder, and H. Kittler, “Automated melanoma recognition,” IEEE transactions on medical imaging, vol. 20, no. 3, pp. 233–239, 2001.PubMed
51.
Zurück zum Zitat C. Grana, G. Pellacani, R. Cucchiara, and S. Seidenari, “A new algorithm for border description of polarized light surface microscopic images of pigmented skin lesions,” IEEE Transactions on Medical Imaging, vol. 22, no. 8, pp. 959–964, 2003.PubMed C. Grana, G. Pellacani, R. Cucchiara, and S. Seidenari, “A new algorithm for border description of polarized light surface microscopic images of pigmented skin lesions,” IEEE Transactions on Medical Imaging, vol. 22, no. 8, pp. 959–964, 2003.PubMed
52.
Zurück zum Zitat P. Rubegni et al., “Automated diagnosis of pigmented skin lesions,” International Journal of Cancer, vol. 101, no. 6, pp. 576–580, 2002.PubMed P. Rubegni et al., “Automated diagnosis of pigmented skin lesions,” International Journal of Cancer, vol. 101, no. 6, pp. 576–580, 2002.PubMed
53.
Zurück zum Zitat F. Ercal, A. Chawla, W. V. Stoecker, H.-C. Lee, and R. H. Moss, “Neural network diagnosis of malignant melanoma from color images,” IEEE Transactions on biomedical engineering, vol. 41, no. 9, pp. 837–845, 1994.PubMed F. Ercal, A. Chawla, W. V. Stoecker, H.-C. Lee, and R. H. Moss, “Neural network diagnosis of malignant melanoma from color images,” IEEE Transactions on biomedical engineering, vol. 41, no. 9, pp. 837–845, 1994.PubMed
54.
Zurück zum Zitat G. R. Lanckriet, T. De Bie, N. Cristianini, M. I. Jordan, and W. S. Noble, “A statistical framework for genomic data fusion,” Bioinformatics, vol. 20, no. 16, pp. 2626–2635, 2004.PubMed G. R. Lanckriet, T. De Bie, N. Cristianini, M. I. Jordan, and W. S. Noble, “A statistical framework for genomic data fusion,” Bioinformatics, vol. 20, no. 16, pp. 2626–2635, 2004.PubMed
55.
Zurück zum Zitat J. Ye et al., “Heterogeneous data fusion for alzheimer’s disease study,” 2008, pp. 1025–1033. J. Ye et al., “Heterogeneous data fusion for alzheimer’s disease study,” 2008, pp. 1025–1033.
56.
Zurück zum Zitat M. Kashani-Sabet et al., “A multimarker prognostic assay for primary cutaneous melanoma,” Clinical Cancer Research, vol. 15, no. 22, pp. 6987–6992, 2009.PubMedPubMedCentral M. Kashani-Sabet et al., “A multimarker prognostic assay for primary cutaneous melanoma,” Clinical Cancer Research, vol. 15, no. 22, pp. 6987–6992, 2009.PubMedPubMedCentral
57.
Zurück zum Zitat G. J. Mann et al., “BRAF mutation, NRAS mutation, and the absence of an immune-related expressed gene profile predict poor outcome in patients with stage III melanoma,” Journal of Investigative Dermatology, vol. 133, no. 2, pp. 509–517, 2013. G. J. Mann et al., “BRAF mutation, NRAS mutation, and the absence of an immune-related expressed gene profile predict poor outcome in patients with stage III melanoma,” Journal of Investigative Dermatology, vol. 133, no. 2, pp. 509–517, 2013.
58.
Zurück zum Zitat B. E. G. Rothberg, M. B. Bracken, and D. L. Rimm, “Tissue biomarkers for prognosis in cutaneous melanoma: a systematic review and meta-analysis,” Journal of the national cancer institute, 2009. B. E. G. Rothberg, M. B. Bracken, and D. L. Rimm, “Tissue biomarkers for prognosis in cutaneous melanoma: a systematic review and meta-analysis,” Journal of the national cancer institute, 2009.
59.
Zurück zum Zitat Z. Xu, Y. Zhou, Y. Cao, T. L. Dinh, J. Wan, and M. Zhao, “Identification of candidate biomarkers and analysis of prognostic values in ovarian cancer by integrated bioinformatics analysis,” Medical oncology (Northwood, London, England), vol. 33, no. 11, p. 130, 2016, https://doi.org/10.1007/s12032-016-0840-y.CrossRef Z. Xu, Y. Zhou, Y. Cao, T. L. Dinh, J. Wan, and M. Zhao, “Identification of candidate biomarkers and analysis of prognostic values in ovarian cancer by integrated bioinformatics analysis,” Medical oncology (Northwood, London, England), vol. 33, no. 11, p. 130, 2016, https://​doi.​org/​10.​1007/​s12032-016-0840-y.CrossRef
62.
Zurück zum Zitat I. Valavanis, I. Maglogiannis, and A. Chatziioannou, “Exploring robust diagnostic signatures for cutaneous melanoma utilizing genetic and imaging data,” IEEE journal of biomedical and health informatics, pp. 190–198, 2015. I. Valavanis, I. Maglogiannis, and A. Chatziioannou, “Exploring robust diagnostic signatures for cutaneous melanoma utilizing genetic and imaging data,” IEEE journal of biomedical and health informatics, pp. 190–198, 2015.
64.
Zurück zum Zitat M. Maragoudakis and I. Maglogiannis, “Skin lesion diagnosis from images using novel ensemble classification techniques,” 2010, pp. 1–5. M. Maragoudakis and I. Maglogiannis, “Skin lesion diagnosis from images using novel ensemble classification techniques,” 2010, pp. 1–5.
65.
Zurück zum Zitat I. Maglogiannis, S. Pavlopoulos, and D. Koutsouris, “An integrated computer supported acquisition, handling, and characterization system for pigmented skin lesions in dermatological images,” IEEE Transactions on Information Technology in Biomedicine, vol. 9, no. 1, pp. 86–98, 2005.PubMed I. Maglogiannis, S. Pavlopoulos, and D. Koutsouris, “An integrated computer supported acquisition, handling, and characterization system for pigmented skin lesions in dermatological images,” IEEE Transactions on Information Technology in Biomedicine, vol. 9, no. 1, pp. 86–98, 2005.PubMed
66.
Zurück zum Zitat G. Kontogianni, O. Papadodima, I. Maglogiannis, K. Frangia-Tsivou, and A. Chatziioannou, “Integrative Bioinformatic Analysis of a Greek Epidemiological Cohort Provides Insight into the Pathogenesis of Primary Cutaneous Melanoma,” 2016. G. Kontogianni, O. Papadodima, I. Maglogiannis, K. Frangia-Tsivou, and A. Chatziioannou, “Integrative Bioinformatic Analysis of a Greek Epidemiological Cohort Provides Insight into the Pathogenesis of Primary Cutaneous Melanoma,” 2016.
68.
Zurück zum Zitat E. Cerami et al., “The cBio cancer genomics portal: an open platform for exploring multidimensional cancer genomics data,” 2012. E. Cerami et al., “The cBio cancer genomics portal: an open platform for exploring multidimensional cancer genomics data,” 2012.
70.
Zurück zum Zitat R. D. Melamed et al., “Genomic characterization of dysplastic nevi unveils implications for diagnosis of melanoma,” Journal of Investigative Dermatology, vol. 137, no. 4, pp. 905–909, 2017. R. D. Melamed et al., “Genomic characterization of dysplastic nevi unveils implications for diagnosis of melanoma,” Journal of Investigative Dermatology, vol. 137, no. 4, pp. 905–909, 2017.
71.
Zurück zum Zitat I. A. Adzhubei et al., “A method and server for predicting damaging missense mutations,” in Nat Methods, vol. 7, United States, 2010, pp. 248–9. I. A. Adzhubei et al., “A method and server for predicting damaging missense mutations,” in Nat Methods, vol. 7, United States, 2010, pp. 248–9.
72.
Zurück zum Zitat T. Koutsandreas, I. Binenbaum, E. Pilalis, I. Valavanis, O. Papadodima, and A. Chatziioannou, “Analyzing and visualizing genomic complexity for the derivation of the emergent molecular networks,” International Journal of Monitoring and Surveillance Technologies Research (IJMSTR), vol. 4, no. 2, pp. 30–49, 2016. T. Koutsandreas, I. Binenbaum, E. Pilalis, I. Valavanis, O. Papadodima, and A. Chatziioannou, “Analyzing and visualizing genomic complexity for the derivation of the emergent molecular networks,” International Journal of Monitoring and Surveillance Technologies Research (IJMSTR), vol. 4, no. 2, pp. 30–49, 2016.
76.
Zurück zum Zitat N. V. Chawla, K. W. Bowyer, L. O. Hall, and W. P. Kegelmeyer, “SMOTE: synthetic minority over-sampling technique,” Journal of artificial intelligence research, vol. 16, pp. 321–357, 2002. N. V. Chawla, K. W. Bowyer, L. O. Hall, and W. P. Kegelmeyer, “SMOTE: synthetic minority over-sampling technique,” Journal of artificial intelligence research, vol. 16, pp. 321–357, 2002.
78.
Zurück zum Zitat R. Development (2011) “Core TeamR: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing,” ISBN 3-900051-07-0. Available: h ttp://www. R-project. org. R. Development (2011) “Core TeamR: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing,” ISBN 3-900051-07-0. Available: h ttp://www. R-project. org.
79.
Zurück zum Zitat M. Kuhn, “Caret: classification and regression training,” Astrophysics Source Code Library, 2015. M. Kuhn, “Caret: classification and regression training,” Astrophysics Source Code Library, 2015.
80.
Zurück zum Zitat L. Torgo, Data mining with R: learning with case studies. CRC press, 2016. L. Torgo, Data mining with R: learning with case studies. CRC press, 2016.
81.
Zurück zum Zitat X. Robin et al., “pROC: an open-source package for R and S+ to analyze and compare ROC curves,” BMC bioinformatics, vol. 12, no. 1, p. 77, 2011.PubMedPubMedCentral X. Robin et al., “pROC: an open-source package for R and S+ to analyze and compare ROC curves,” BMC bioinformatics, vol. 12, no. 1, p. 77, 2011.PubMedPubMedCentral
82.
Zurück zum Zitat K. Hajian-Tilaki, “Receiver Operating Characteristic (ROC) Curve Analysis for Medical Diagnostic Test Evaluation,” Caspian journal of internal medicine, vol. 4, no. 2, pp. 627–35, Spring 2013.PubMedPubMedCentral K. Hajian-Tilaki, “Receiver Operating Characteristic (ROC) Curve Analysis for Medical Diagnostic Test Evaluation,” Caspian journal of internal medicine, vol. 4, no. 2, pp. 627–35, Spring 2013.PubMedPubMedCentral
83.
Zurück zum Zitat Brooke, J., “SUS – A Quick and Dirty Usability Scale,” in Usability Evaluation in Industry, vol. 194, 1996, pp. 4–7. Brooke, J., “SUS – A Quick and Dirty Usability Scale,” in Usability Evaluation in Industry, vol. 194, 1996, pp. 4–7.
84.
Zurück zum Zitat Brooke, J., “SUS: a retrospective,” Journal of usability studies, vol. 8, no. 2, pp. 29–40, 2013. Brooke, J., “SUS: a retrospective,” Journal of usability studies, vol. 8, no. 2, pp. 29–40, 2013.
Metadaten
Titel
An Integrated Platform for Skin Cancer Heterogenous and Multilayered Data Management
verfasst von
Ilias Maglogiannis
Georgia Kontogianni
Olga Papadodima
Haralampos Karanikas
Antonis Billiris
Aristotelis Chatziioannou
Publikationsdatum
01.01.2021
Verlag
Springer US
Erschienen in
Journal of Medical Systems / Ausgabe 1/2021
Print ISSN: 0148-5598
Elektronische ISSN: 1573-689X
DOI
https://doi.org/10.1007/s10916-020-01679-3