Modern medical diagnosis, treatment, or rehabilitation problems of the patient reach completely different levels due to the rapid development of artificial intelligence tools. Methods of machine learning and optimization based on the intersection of historical data of various volumes provide significant support to physicians in the form of accurate and fast solutions of automated diagnostic systems. It significantly improves the quality of medical services. This special issue deals with the problems of medical diagnosis and prognosis in the case of short datasets. The problem is not new, but existing machine learning methods do not always demonstrate the adequacy of prediction or classification models, especially in the case of limited data to implement the training procedures. That is why the improvement of existing and development of new artificial intelligence tools that will be able to solve it effectively is an urgent task. The special issue contains the latest achievements in medical diagnostics based on the processing of small numerical and image-based datasets. Described methods have a strong theoretical basis, and numerous experimental studies confirm the high efficiency of their application in various applied fields of Medicine.
Citation: Ivan Izonin, Nataliya Shakhovska. Special issue: informatics & data-driven medicine-2021[J]. Mathematical Biosciences and Engineering, 2022, 19(10): 9769-9772. doi: 10.3934/mbe.2022454
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Modern medical diagnosis, treatment, or rehabilitation problems of the patient reach completely different levels due to the rapid development of artificial intelligence tools. Methods of machine learning and optimization based on the intersection of historical data of various volumes provide significant support to physicians in the form of accurate and fast solutions of automated diagnostic systems. It significantly improves the quality of medical services. This special issue deals with the problems of medical diagnosis and prognosis in the case of short datasets. The problem is not new, but existing machine learning methods do not always demonstrate the adequacy of prediction or classification models, especially in the case of limited data to implement the training procedures. That is why the improvement of existing and development of new artificial intelligence tools that will be able to solve it effectively is an urgent task. The special issue contains the latest achievements in medical diagnostics based on the processing of small numerical and image-based datasets. Described methods have a strong theoretical basis, and numerous experimental studies confirm the high efficiency of their application in various applied fields of Medicine.
| [1] | N. Shakhovska, A. Salazar, I. Izonin, J. Campos, IDDM 2021: Proceedings of the 4th International Conference on Informatics & Data-Driven Medicine Valencia, Spain, November 19-21, 2021, CEUR-WS.org, 2021, 3038. Available from: http://ceur-ws.org/Vol-3038/ |
| [2] |
X. Liu, V. Krylov, S. Jun, N. Volkova, A. Sachenko, G. Shcherbakova, et al., Segmentation and identification of spectral and statistical textures for computer medical diagnostics in dermatology, Math. Biosci. Eng., 19 (2022), 6923-6939. https://doi.org/10.3934/mbe.2022326 doi: 10.3934/mbe.2022326
|
| [3] |
Y. Bodyanskiy, O. Chala, N. Kasatkina, I. Pliss, Modified generalized neo-fuzzy system with combined online fast learning in medical diagnostic task for situations of information deficit, Math. Biosci. Eng., 19 (2022), 8003-8018. https://doi.org/10.3934/mbe.2022374 doi: 10.3934/mbe.2022374
|
| [4] |
R. Loula, L. H. A. Monteiro, On the criteria for diagnosing depression in bereaved individuals: a self-organizing map approach, Math. Biosci. Eng., 19 (2022), 5380-5392. https://doi.org/10.3934/mbe.2022252 doi: 10.3934/mbe.2022252
|
| [5] |
L-S. Lin, S. C. Hu, Y-S. Lin, D. C. Li, L. R. Siao, A new approach to generating virtual samples to enhance classification accuracy with small data—a case of bladder cancer, Math. Biosci. Eng., 19 (2022), 6204-6233. https://doi.org/10.3934/mbe.2022290 doi: 10.3934/mbe.2022290
|
| [6] |
N. Shakhovska, V. Yakovyna, V. Chopyak, A new hybrid ensemble machine-learning model for severity risk assessment and post-COVID prediction system, Math. Biosci. Eng., 19 (2022), 6102-6123. https://doi.org/10.3934/mbe.2022285 doi: 10.3934/mbe.2022285
|
| [7] |
Y. Hu, M. Wang, K. Wang, J. Gao, J. Tong, Z. Zhao, et al., A potential role for metastasis-associated in colon cancer 1 (MACC1) as a pan-cancer prognostic and immunological biomarker, Math. Biosci. Eng., 19 (2022), 8331-8353. https://doi.org/10.3934/mbe.2021413 doi: 10.3934/mbe.2021413
|
| [8] |
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|
| [9] |
S. Shandilya, I. Izonin, S. K. Shandilya, K. K. Singh, Mathematical modelling of bio-inspired frog leap optimization algorithm for transmission expansion planning, Math. Biosci. Eng., 19 (2022), 7232-7247. https://doi.org/10.3934/mbe.2022341 doi: 10.3934/mbe.2022341
|
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| 2. | Tamar Friedlander, Roshan Prizak, Călin C. Guet, Nicholas H. Barton, Gašper Tkačik, Intrinsic limits to gene regulation by global crosstalk, 2016, 7, 2041-1723, 10.1038/ncomms12307 | |
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Ivan Izonin, Nataliya Shakhovska. Special issue: informatics & data-driven medicine-2021[J]. Mathematical Biosciences and Engineering, 2022, 19(10): 9769-9772. doi: 10.3934/mbe.2022454
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