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Заглавие: | A survey of the potentials of model-based reinforcement learning algorithms in medicine |
Автори: | Abdulhameed, Abubakar Sadiq Lupenko, S. |
Affiliation: | Ternopil Ivan Puluj National Technical University, Ruska 56, Ternopil, Ukraine |
Bibliographic description (Ukraine): | Abdulhameed A. S. A survey of the potentials of model-based reinforcement learning algorithms in medicine / Abubakar Sadiq Abdulhameed, S. Lupenko // Proceedings of the scientific and technical conference "Information models, systems and technologies", 08-09 December 2021. — Tern. : TNTU, 2021. — P. 107. — (Комп’ютерні системи та мережі). |
Bibliographic description (International): | Abdulhameed A. S., Lupenko S. (2021) A survey of the potentials of model-based reinforcement learning algorithms in medicine. Proceedings of the scientific and technical conference "Information models, systems and technologies" (Tern., 08-09 December 2021), pp. 107. |
Is part of: | Матеріали Ⅸ науково-технічної конференції „Інформаційні моделі, системи та технології“, 2021 Proceedings of the scientific and technical conference "Information models, systems and technologies", 2021 |
Conference/Event: | Ⅸ науково-технічна конференція „Інформаційні моделі, системи та технології“ |
Journal/Collection: | Матеріали Ⅸ науково-технічної конференції „Інформаційні моделі, системи та технології“ |
Дата на Публикуване: | 8-Дек- 21 |
Date of entry: | 23-Мар-2022 |
Издател: | ТНТУ TNTU |
Place of the edition/event: | Тернопіль Ternopil |
Temporal Coverage: | 08-09 грудня 2021 року 08-09 December 2021 |
Number of pages: | 1 |
Page range: | 107 |
Start page: | 107 |
End page: | 107 |
Резюме: | Contemporary reinforcement learning research teams have made remarkable progress in games and comparatively less in the medical field. Most recent implementations of reinforcement learning are focused on model-free learning algorithms as they are relatively easier to implement. This paper seeks to present model-based reinforcement learning notions, and articulate how model-based learning can be efficient in medical image processing in juxtaposition to model-free learning. |
URI: | http://elartu.tntu.edu.ua/handle/lib/37654 |
Copyright owner: | © Тернопільський національний технічний університет імені Івана Пулюя, 2021 |
URL for reference material: | https://www.ctoam.com/precision-oncology/why-we-exist/standard-treatment/diagnostics/ct-scan/ |
References (International): | 1. Micheal Kirsch. When a CT scan misses cancer. KeninMD, April 26, 2015. URL: https://www.ctoam.com/precision-oncology/why-we-exist/standard-treatment/diagnostics/ct-scan/. 2. Mnih V, Kavukcuoglu K, Silver D, Rusu AA, Veness J, Bellemare MG, et al. Human-level control through deep reinforcement learning. Nature. 2015 Feb; 518(7540): 529–33. |
Content type: | Conference Abstract |
Показва се в Колекции: | IX науково-технічна конференція „Інформаційні моделі, системи та технології“ (2021) |
Файлове в Този Публикация:
Файл | Описание | Размер | Формат | |
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IMST_2021_Abdulhameed_A_S-A_survey_of_the_potentials_107.pdf | 165,38 kB | Adobe PDF | Изглед/Отваряне | |
IMST_2021_Abdulhameed_A_S-A_survey_of_the_potentials_107.djvu | 17,98 kB | DjVu | Изглед/Отваряне | |
IMST_2021_Abdulhameed_A_S-A_survey_of_the_potentials_107__COVER.png | 466,19 kB | image/png | Изглед/Отваряне |
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