Zobrazeno 1 - 10
of 3 627
pro vyhledávání: '"medical image analysis"'
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-13 (2024)
Abstract Skin Cancer, which leads to a large number of deaths annually, has been extensively considered as the most lethal tumor around the world. Accurate detection of skin cancer in its early stage can significantly raise the survival rate of patie
Externí odkaz:
https://doaj.org/article/a36ea96df65f4c47987beea86067eaec
Autor:
Ece Ozkan, Xavier Boix
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-15 (2024)
Abstract Current machine learning methods for medical image analysis primarily focus on developing models tailored for their specific tasks, utilizing data within their target domain. These specialized models tend to be data-hungry and often exhibit
Externí odkaz:
https://doaj.org/article/0307af70b26743739d37c7a65ca1a464
Publikováno v:
Jurnal Saintekom, Vol 14, Iss 2, Pp 195-207 (2024)
This study aims to evaluate the effectiveness and efficiency of various deep learning models in recognizing patterns within diverse biomedical datasets. The methods involved the collection of biomedical data from various public and synthetic sources,
Externí odkaz:
https://doaj.org/article/ff2140175c7540d182f97643b8cb4589
Autor:
Ievgen A. Nastenko, Maksym O. Honcharuk, Vitalii O. Babenko, Mykola I. Lynnyk, Viktoria I. Ignatieva, Vitalii A. Yachnyk
Publikováno v:
Український журнал серцево-судинної хірургії, Vol 32, Iss 3, Pp 58-65 (2024)
It has been established that 7.2% of patients hospitalized with coronavirus disease (COVID-19) exhibit signs of heart disease, with 23% of these patients experiencing heart failure. Currently, there is a lack of data on chest computed tomography (CT)
Externí odkaz:
https://doaj.org/article/a6cec53de9554105abc296288c140ca5
Autor:
Dost Muhammad, Malika Bendechache
Publikováno v:
Computational and Structural Biotechnology Journal, Vol 24, Iss , Pp 542-560 (2024)
This systematic literature review examines state-of-the-art Explainable Artificial Intelligence (XAI) methods applied to medical image analysis, discussing current challenges and future research directions, and exploring evaluation metrics used to as
Externí odkaz:
https://doaj.org/article/919c157942e74315bf2f9fec3bcf7873
Publikováno v:
Computational and Structural Biotechnology Journal, Vol 23, Iss , Pp 669-678 (2024)
With the advent of digital pathology and microscopic systems that can scan and save whole slide histological images automatically, there is a growing trend to use computerized methods to analyze acquired images. Among different histopathological imag
Externí odkaz:
https://doaj.org/article/3560b1796cfa4b1e93039f111cfd902f
Autor:
Sonam Aggarwal, Isha Gupta, Ashok Kumar, Sandeep Kautish, Abdulaziz S. Almazyad, Ali Wagdy Mohamed, Frank Werner, Mohammad Shokouhifar
Publikováno v:
Mathematical Biosciences and Engineering, Vol 21, Iss 8, Pp 6847-6869 (2024)
Convolutional Neural Networks (CNNs) have received substantial attention as a highly effective tool for analyzing medical images, notably in interpreting endoscopic images, due to their capacity to provide results equivalent to or exceeding those of
Externí odkaz:
https://doaj.org/article/9032ca46eee542d1a07eaaefc0f1d119
Publikováno v:
Journal of Modern Science, Vol 57, Iss 3, Pp 757-771 (2024)
This work aims to implement and utilize an advanced computer system for image analysis and processing through artificial intelligence. The system will evaluate images from multiple sources. As a result, a comprehensive e-Medicus system will be develo
Externí odkaz:
https://doaj.org/article/80b49f88ebdf4b00a15d7b5a1fb4c98a
Autor:
Ashish Singh Chauhan, Rajesh Singh, Neeraj Priyadarshi, Bhekisipho Twala, Surindra Suthar, Siddharth Swami
Publikováno v:
Discover Artificial Intelligence, Vol 4, Iss 1, Pp 1-26 (2024)
Abstract This study explores the practical applications of artificial intelligence (AI) in medical imaging, focusing on machine learning classifiers and deep learning models. The aim is to improve detection processes and diagnose diseases effectively
Externí odkaz:
https://doaj.org/article/e75c8815a7294289a49c984d5c7cc3c3
Autor:
Masaki Morishita, Hikaru Fukuda, Kosuke Muraoka, Taiji Nakamura, Masanari Hayashi, Izumi Yoshioka, Kentaro Ono, Shuji Awano
Publikováno v:
Journal of Dental Sciences, Vol 19, Iss 3, Pp 1595-1600 (2024)
Background/purpose: Rapid advancements in AI technology have led to significant interest in its application across various fields, including medicine and dentistry. This study aimed to assess the capabilities of ChatGPT-4V with image recognition in a
Externí odkaz:
https://doaj.org/article/1aab5840951f435aa8da0a2a4c2abb00