Zobrazeno 1 - 10
of 216
pro vyhledávání: ''
Autor:
Narongrid Seesawad, Piyalitt Ittichaiwong, Thapanun Sudhawiyangkul, Phattarapong Sawangjai, Peti Thuwajit, Paisarn Boonsakan, Supasan Sripodok, Kanyakorn Veerakanjana, Komgrid Charngkaew, Ananya Pongpaibul, Napat Angkathunyakul, Narit Hnoohom, Sumeth Yuenyong, Chanitra Thuwajit, Theerawit Wilaiprasitporn
Publikováno v:
IEEE Open Journal of Engineering in Medicine and Biology, Vol 5, Pp 514-523 (2024)
Background: Deep learning models for patch classification in whole-slide images (WSIs) have shown promise in assisting follicular lymphoma grading. However, these models often require pathologists to identify centroblasts and manually provide refined
Externí odkaz:
https://doaj.org/article/0c94c612c58b45a59a13709fb48791dd
Autor:
Sabrina Zumbo, Stefano Mandija, Ettore F. Meliado, Peter Stijnman, Thierry G. Meerbothe, Cornelis A.T. van den Berg, Tommaso Isernia, Martina T. Bevacqua
Publikováno v:
IEEE Open Journal of Engineering in Medicine and Biology, Vol 5, Pp 505-513 (2024)
Magnetic Resonance imaging based Electrical Properties Tomography (MR-EPT) is a non-invasive technique that measures the electrical properties (EPs) of biological tissues. In this work, we present and numerically investigate the performance of an unr
Externí odkaz:
https://doaj.org/article/b2bccd4ee1b74e24a32c9dbc86bac947
Autor:
A. Scotland, G. Cosne, A. Juraver, A. Karatsidis, J. Penalver-Andres, E. Bartholome, C. M. Kanzler, C. Mazza, D. Roggen, C. Hinchliffe, S. Del Din, S. Belachew
Publikováno v:
IEEE Open Journal of Engineering in Medicine and Biology, Vol 5, Pp 494-497 (2024)
Goal: This paper introduces DISPEL, a Python framework to facilitate development of sensor-derived measures (SDMs) from data collected with digital health technologies in the context of therapeutic development for neurodegenerative diseases. Methods:
Externí odkaz:
https://doaj.org/article/bdf54615385840dc83608c9415584320
Autor:
Sofia Poletto, Emanuela Zannin, Emanuele Ghilotti, Giovanni Putoto, Jerry Ichto, Peter Lochoro, Moses Obizu, Samuel Okori, Matteo Corno, Raffaele L Dellaca
Publikováno v:
IEEE Open Journal of Engineering in Medicine and Biology, Vol 5, Pp 498-504 (2024)
Goal: To develop and validatea novel neonatal non-invasive respiratory support device prototype designed to operate in low-resource settings. Methods: The device integrates a blower-based ventilator and a portable oxygen concentrator. A novel control
Externí odkaz:
https://doaj.org/article/dab89abad9f74073a2d547be1636e6d9
Autor:
Simar P. Singh, Amir Mehdi Shayan, Jianxin Gao, Joseph Bible, Richard E. Groff, Ravikiran Singapogu
Publikováno v:
IEEE Open Journal of Engineering in Medicine and Biology, Vol 5, Pp 485-493 (2024)
Goal: Vascular surgical procedures are challenging and require proficient suturing skills. To develop these skills, medical training simulators with objective feedback for formative assessment are gaining popularity. As hardware advancements offer mo
Externí odkaz:
https://doaj.org/article/de9b994ae7f547d18b533038d6e12df5
Publikováno v:
IEEE Open Journal of Engineering in Medicine and Biology, Vol 5, Pp 396-403 (2024)
Goal: As an essential human-machine interactive task, emotion recognition has become an emerging area over the decades. Although previous attempts to classify emotions have achieved high performance, several challenges remain open: 1) How to effectiv
Externí odkaz:
https://doaj.org/article/4d724c47499a483da4d4393346854a3f
Autor:
Andrea Cafarelli, Angela Sorriento, Giorgia Marola, Denise Amram, Fabien Rabusseau, Herve Locteau, Paolo Cabras, Erik Dumont, Sam Nakhaei, Ake Jernberger, Par Bergsten, Paolo Spinnato, Alessandro Russo, Leonardo Ricotti
Publikováno v:
IEEE Open Journal of Engineering in Medicine and Biology, Vol 5, Pp 476-484 (2024)
Goal: To evaluate the usability of different technologies designed for a remote assessment of knee osteoarthritis. Methods: We recruited eleven patients affected by mild or moderate knee osteoarthritis, eleven caregivers, and eleven clinicians to ass
Externí odkaz:
https://doaj.org/article/993c646b55194fc9978c945da8efb0be
Publikováno v:
IEEE Open Journal of Engineering in Medicine and Biology, Vol 5, Pp 404-420 (2024)
Goal: Augment a small, imbalanced, wound dataset by using semi-supervised learning with a secondary dataset. Then utilize the augmented wound dataset for deep learning-based wound assessment. Methods: The clinically-validated Photographic Wound Asses
Externí odkaz:
https://doaj.org/article/0dd534e396e0400a8669feb4673feb1a
Publikováno v:
IEEE Open Journal of Engineering in Medicine and Biology, Vol 5, Pp 459-466 (2024)
Goal: Deep learning techniques have made significant progress in medical image analysis. However, obtaining ground truth labels for unlabeled medical images is challenging as they often outnumber labeled images. Thus, training a high-performance mode
Externí odkaz:
https://doaj.org/article/85f6a349f1b4466da4c967a3ec49620b
Publikováno v:
IEEE Open Journal of Engineering in Medicine and Biology, Vol 5, Pp 428-433 (2024)
Goal: The purpose of this paper is to recognize autism spectrum disorders (ASD) using graph attention network. Methods: we propose a node features graph attention network (NF-GAT) for learning functional connectivity (FC) features to achieve ASD diag
Externí odkaz:
https://doaj.org/article/42110df3d4ad4889b45d401d4b37aa43