PREŠOVSKÁ UNIVERZITA V PREŠOVE
UNIVERZITNÁ KNIŽNICA
UNIVERZITNÁ KNIŽNICA
| ID záznamu: | 205407 |
|---|---|
| Kategória: | ADC |
| Autor: | Sabol Patrik (20%) |
| Autor: | Sinčák Peter (20%) |
| Autor: | Hartono Pitoyo (5%) |
| Autor: | Kočan Pavel (15%) |
| Autor: | Benetinová Zuzana (5%) |
| Autor: | Blichárová Alžbeta (5%) |
| Autor: | Verbóová Ľudmila (5%) |
| Autor: | Štammová Erika (5%) |
| Autor: | Sabolová Fabianová Antónia (10%) |
| Autor: | Jašková Anna (10%) |
| Názov: | Explainable classifier for improving the accountability in decision-making for colorectal cancer diagnosis from histopathological images [elektronický dokument] |
| Zdroj: | Journal of biomedical informatics [print, elektronický dokument] |
| Lokácia: | Roč. 109. - San Diego, (2020), s. 1-10 |
| ISSN: | 1532-0464. - ISSN 1532-0480 |
| URL: | https://doi.org/10.1016/j.jbi.2020.103523 |
| Ohlas: | [1] 2021. NGUYEN, Huu Giao, BLANK, Annika, DAWSON, Heather E. et al. Classification of colorectal tissue images from high throughput tissue microarrays by ensemble deep learning methods. In Scientific Reports : print, elektronický dokument, ISSN 2045-2322. Londýn, 2021, Roč. 11, č. 1. SCO. |
| Ohlas: | [1] 2020. DEBELEE, Taye Girma, KEBEDE, Samuel Rahimeto, SCHWENKER, Friedhelm et al. Deep learning in selected cancers' image analysis-a survey. In Journal of imaging : elektronický dokument, ISSN 2313-433X. Basel, 2020, Roč. 6, č. 11. |
| Ohlas: | [1] 2021. OLIVEIRA, Sara P., NETO, Pedro C., FRAGA, João et al. CAD systems for colorectal cancer from WSI are still not ready for clinical acceptance. In Scientific Reports : print, elektronický dokument, ISSN 2045-2322. Londýn, 2021, Roč. 11, č. 1. SCO. |
| Ohlas: | [1] 2021. FAROUQ, Muhamed Wael, BOULILA, Wadii, HUSSAIN, Zain et al. A novel coupled reaction-diffusion system for explainable gene expression profiling. In Sensors : print, elektronický dokument, ISSN 1424-8220; 1424-3210. Bazilej, 2021, Roč. 21, č. 6, 1-20. SCO. |
| Ohlas: | [1] 2021. BOROWA, Adriana, RYMARCZYK, Dawid, OCHONSKA, Dorota et al. Deep learning classification of bacteria clones explained by persistence homology. In Proceedings of the International Joint Conference on Neural Networks. 2021. ISBN 9780738133669. |
| Ohlas: | [1] 2021. CASTILLO-SECILLA, Daniel, GÁLVEZ, Juan Manuel, CARRILLO-PEREZ, Francisco et al. KnowSeq R-Bioc package: The automatic smart gene expression tool for retrieving relevant biological knowledge. In Computers in Biology and Medicine : print, elektronický dokument, ISSN 0010-4825; 1879-0534. Amsterdam, 2021, Roč. 133. SCO ; CCC ; WOS CC. |
| Ohlas: | [1] 2021. MINH, Dang, WANG, H. Xiang, LI, Y. Fen et al. Explainable artificial intelligence: a comprehensive review. In Artificial Intelligence Review : print, ISSN 0269-2821; 1573-7462. 2021. |
| Ohlas: | [1] 2021. GALLO, Peter, BALOGOVÁ, Beáta, ČABINOVÁ, Veronika et al. The perception of gender stereotypes in managerial positions of industrial companies. In Polish Journal of Management Studies : print, elektronický dokument, ISSN 2081-7452. Czestochowa, 2021, Roč. 23, č. 2, s. 149-164. SCO. |
| Ohlas: | [1] 2021. KATE, Vandana, SHUKLA, Pragya. A new approach to breast cancer analysis through histopathological images using MI, MD binary, and eight class classifying techniques. In Journal of Ambient Intelligence and Humanized Computing : print, elektronický dokument, ISSN 1868-5137; 1868-5145. 2021. |
| Ohlas: | [1] 2021. XU, Xi, LI, Jianqiang, GUAN, Yu et al. GLA-Net: A global-local attention network for automatic cataract classification. In Journal of biomedical informatics : print, elektronický dokument, ISSN 1532-0464; 1532-0480. San Diego, 2021, Roč. 124. |
| Ohlas: | [1] 2021. DE SOUZA, Luis A., MENDEL, Robert, STRASSER, Sophia et al. Convolutional Neural Networks for the evaluation of cancer in Barrett's esophagus: Explainable AI to lighten up the black-box. In Computers in Biology and Medicine : print, elektronický dokument, ISSN 0010-4825; 1879-0534. Amsterdam, 2021, Roč. 135. SCO ; CCC ; WOS CC. |
| Ohlas: | [3] 2022. KHALID, F., PARSAD, P.W.C., NIZAMANI, Q.U.A. et al. Review of performance analysis technique of high-resolution imaging in mobile telemedicine system. In Proceedings of the ICR’22 international conference on innovations in computing research. Cham : Springer, 2022, s. 142. ISBN 978-3-031-14053-2. |
| Ohlas: | [3] 2022. AWOTUNDE, J.B., ADENIYI, E.A., AJAMU, G.J. et al. Explainable artificial intelligence in genomic sequence for healthcare systems prediction. In Connected e-Health : integrated loT and loud computing. Cham : Springer, 2022, s. 435. ISBN 978-3-030-97928-7. |
| Ohlas: | [1] 2023. JUNG, J.S., LEE, H.Y.B., JUNG, H. et al. Essential properties and explanation effectiveness of explainable artificial intelligence in healthcare: a systematic review. In Heliyon, ISSN 2405-8440. 2023, roč. 9, č. 5, art. no. e16110. WOS:001042435100001. |
| Ohlas: | [1] 2022. LIU, C.F., CHEN, Z.C., KUO, S.C. et al. Does AI explainability affect physicians? Intention to use AI?. In International journal of medical informatics, ISSN 1386-5056. 2022, roč. 168, art. no. 104884. WOS:000875654700002. |
| Ohlas: | [1] 2022. SEXAUER, R., BESTLER, C. Time is money: considerations for measuring the radiological reading time. In Journal of imaging, ISSN 2313-433X. 2022, roč. 8, č. 8, art. no. 208. WOS:000846534600001. |
| Ohlas: | [1] 2022. KAVITHA, M.S., GANGADARAN, P., JACKSON, A. et al. Deep neural network models for colon cancer screening. In Cancers, ISSN 2072-6694. 2022, roč. 14, č. 15, art. no. 3707. WOS:000840169900001. |
| Ohlas: | [1] 2022. BUCHSBAUM, J.C., JAFFRAY, D.A., BA, D.B. et al. Predictive radiation oncology - A new NCI-DOE scientific space and community. In Radiation research, ISSN 0033-7587. 2022, roč. 197, č. 4, s. 434-445. WOS:000778439000012. |
| Ohlas: | [1] 2023. S BAND, S., YARAHMADI, A., HSU, Ch. et al. Application of explainable artificial intelligence in medical health: a systematic review of interpretability methods. In Informatics in medicine unlocked, ISSN 2352-9148. 2023, roč. 40, art. no. 101286. SCOPUS. |
| Ohlas: | [1] 2023. SUN, S., WU, J., YAO, J. et al. Rectal cancer stages T2 and T3 identification based on asymptotic hybrid feature maps. In CMES - Computer modeling in engineering and sciences, ISSN 1526-1492. 2023, roč. 137, č. 1, s. 923-938. SCOPUS; WOS:001048296200018. |
| Oblasť výskumu: | 170 |
| Oblasť výskumu: | 060 |
| Oblasť výskumu: | 180 |
| Oblasť výskumu: | 160 |
