Zobrazeno 1 - 10
of 4 470
pro vyhledávání: '"Alessa A"'
Autor:
Albalawi Karma, Panneerselvam Chellasamy, Moawadh Mamdoh S., Alalawy Adel I., Omran Awatif M. E., Abdelaziz Mahmoud A., Mohammedsaleh Zuhair M., Al-Aoh Hatem A., Mustafa Syed Khalid, Keshk Ali A., Al-Morwani Majed M., Alessa Ali Hamzah, Al-Anazi Menier, Khateeb Sahar
Publikováno v:
e-Polymers, Vol 23, Iss 1, Pp 209-49 (2023)
Surgery, chemotherapy, and radiation therapy are all forms of cancer treatment, as well as more recent methods including interventional radiology and immunotherapy. In this study, we synthesize a novel chitosan (CH) nanocomplex (NC)-based polysacchar
Externí odkaz:
https://doaj.org/article/6427e08e34514b0294c75fa49a11500d
Autor:
João Luiz Veloso Mourão, Alessa Andrade Santana, Marcelo de Carvalho Ramos, Lucieni Conterno, Fabiano Reis
Publikováno v:
Revista da Sociedade Brasileira de Medicina Tropical, Vol 56 (2023)
Externí odkaz:
https://doaj.org/article/8d55a118e4324d1ab458a01d85646e0f
Publikováno v:
Biomédica: revista del Instituto Nacional de Salud, Vol 42, Iss 4, Pp 602-610 (2022)
Introduction: The use of technological resources to support processes in health systems has generated robust, interoperable and dynamic platforms. In the case of institutions working with neglected tropical diseases (NTD), there is a need for NTD-spe
Externí odkaz:
https://doaj.org/article/0388bf88713a4b6c829c1d9b3c2bc468
Autor:
Anna Saranti, Miroslav Hudec, Erika Mináriková, Zdenko Takáč, Udo Großschedl, Christoph Koch, Bastian Pfeifer, Alessa Angerschmid, Andreas Holzinger
Publikováno v:
Machine Learning and Knowledge Extraction, Vol 4, Iss 4, Pp 924-953 (2022)
In many domains of our daily life (e.g., agriculture, forestry, health, etc.), both laymen and experts need to classify entities into two binary classes (yes/no, good/bad, sufficient/insufficient, benign/malign, etc.). For many entities, this decisio
Externí odkaz:
https://doaj.org/article/ec0de37f48924e4c8364acae29f28630
Publikováno v:
Machine Learning and Knowledge Extraction, Vol 4, Iss 2, Pp 556-579 (2022)
AI-assisted decision-making that impacts individuals raises critical questions about transparency and fairness in artificial intelligence (AI). Much research has highlighted the reciprocal relationships between the transparency/explanation and fairne
Externí odkaz:
https://doaj.org/article/639332d9dfa0497ab1fdd147631b6285
Medical image analysis tasks often focus on regions or structures located in a particular location within the patient's body. Often large parts of the image may not be of interest for the image analysis task. When using deep-learning based approaches
Externí odkaz:
http://arxiv.org/abs/2410.02316
This paper is devoted to studying the optical and thermal geometrical properties of Hot, NUT-KerrNewman-Kasuya-AdS black hole (BH). This BH is characterized by the NUT charge and a parameter Q that comprises the electric and magnetic charge. We compu
Externí odkaz:
http://arxiv.org/abs/2408.04365
Autor:
Bhattarai, Binod, Loebman, Sarah R., Ness, Melissa K., Wetzel, Andrew, Cunningham, Emily C., Parul, Hanna, Wiggins, Alessa Ibrahim
Open star clusters are the essential building blocks of the Galactic disk; "strong chemical tagging" - the premise that all star clusters can be reconstructed given chemistry information alone - is a driving force behind many current and upcoming lar
Externí odkaz:
http://arxiv.org/abs/2408.02228
Autor:
Häntze, Hartmut, Xu, Lina, Dorfner, Felix J., Donle, Leonhard, Truhn, Daniel, Aerts, Hugo, Prokop, Mathias, van Ginneken, Bram, Hering, Alessa, Adams, Lisa C., Bressem, Keno K.
Purpose: To introduce a deep learning model capable of multi-organ segmentation in MRI scans, offering a solution to the current limitations in MRI analysis due to challenges in resolution, standardized intensity values, and variability in sequences.
Externí odkaz:
http://arxiv.org/abs/2405.06463
Autor:
Häntze, Hartmut, Xu, Lina, Rattunde, Maximilian, Donle, Leonhard, Dorfner, Felix J., Hering, Alessa, Adams, Lisa C., Bressem, Keno K.
Computed tomography (CT) segmentation models often contain classes that are not currently supported by magnetic resonance imaging (MRI) segmentation models. In this study, we show that a simple image inversion technique can significantly improve the
Externí odkaz:
http://arxiv.org/abs/2405.03713