Results 51 to 60 of about 496,139 (318)

Bioengineering facets of the tumor microenvironment in 3D tumor models: insights into cellular, biophysical and biochemical interactions

FEBS Open Bio, EarlyView.
The tumor microenvironment is a dynamic, multifaceted complex system of interdependent cellular, biochemical, and biophysical components. Three‐dimensional in vitro models of the tumor microenvironment enable a better understanding of these interactions and their impact on cancer progression and therapeutic resistance.
Salma T. Rafik, Deniz Bakkalci, Alexander J. MacRobert, Umber Cheema   +3 more
wiley   +1 more source

MD-Unet for tobacco leaf disease spot segmentation based on multi-scale residual dilated convolutions

Scientific Reports
Identification and diagnosis of tobacco diseases are prerequisites for the scientific prevention and control of these ailments. To address the limitations of traditional methods, such as weak generalization and sensitivity to noise in segmenting tobacco ...
Zili Chen, Yilong Peng, Jiadong Jiao, Aiguo Wang, Laigang Wang, Wei Lin, Yan Guo   +6 more
doaj   +1 more source

Enhanced dose prediction for head and neck cancer artificial intelligence‐driven radiotherapy based on transfer learning with limited training data

Journal of Applied Clinical Medical Physics, EarlyView.
Abstract Purpose Training deep learning dose prediction models for the latest cutting‐edge radiotherapy techniques, such as AI‐based nodal radiotherapy (AINRT) and Daily Adaptive AI‐based nodal radiotherapy (DA‐AINRT), is challenging due to limited data.
Hui‐Ju Wang, Austen Maniscalco, David Sher, Mu‐Han Lin, Steve Jiang, Dan Nguyen   +5 more
wiley   +1 more source

A review of artificial intelligence in brachytherapy

Journal of Applied Clinical Medical Physics, EarlyView.
Abstract Artificial intelligence (AI) has the potential to revolutionize brachytherapy's clinical workflow. This review comprehensively examines the application of AI, focusing on machine learning and deep learning, in various aspects of brachytherapy.
Jingchu Chen, Richard L. J. Qiu, Tonghe Wang, Shadab Momin, Xiaofeng Yang   +4 more
wiley   +1 more source

Unsupervised Person Re-Identification: A Systematic Survey of Challenges and Solutions [PDF]

arXiv, 2021
Person re-identification (Re-ID) has been a significant research topic in the past decade due to its real-world applications and research significance. While supervised person Re-ID methods achieve superior performance over unsupervised counterparts, they can not scale to large unlabelled datasets and new domains due to the prohibitive labelling cost ...
arxiv  

Closing the gap in plan quality: Leveraging deep‐learning dose prediction for adaptive radiotherapy

Journal of Applied Clinical Medical Physics, EarlyView.
Abstract Purpose Balancing quality and efficiency has been a challenge for online adaptive therapy. Most systems start the online re‐optimization with the original planning goals. While some systems allow planners to modify the planning goals, achieving a high‐quality plan within time constraints remains a common barrier.
Sean J. Domal, Austen Maniscalco, Justin Visak, Michael Dohopolski, Dominic Moon, Vladimir Avkshtol, Dan Nguyen, Steve Jiang, David Sher, Mu‐ Han Lin   +9 more
wiley   +1 more source

Digital twins to personalize medicine

Genome Medicine, 2019
Personalized medicine requires the integration and processing of vast amounts of data. Here, we propose a solution to this challenge that is based on constructing Digital Twins.
Bergthor Björnsson, Carl Borrebaeck, Nils Elander, Thomas Gasslander, Danuta R. Gawel, Mika Gustafsson, Rebecka Jörnsten, Eun Jung Lee, Xinxiu Li, Sandra Lilja, David Martínez-Enguita, Andreas Matussek, Per Sandström, Samuel Schäfer, Margaretha Stenmarker, X. F. Sun, Oleg Sysoev, Huan Zhang, Mikael Benson, on behalf of the Swedish Digital Twin Consortium   +19 more
doaj   +1 more source

Context-Aware Unsupervised Clustering for Person Search [PDF]

arXiv, 2021
The existing person search methods use the annotated labels of person identities to train deep networks in a supervised manner that requires a huge amount of time and effort for human labeling. In this paper, we first introduce a novel framework of person search that is able to train the network in the absence of the person identity labels, and propose
arxiv  

Toward a human‐centric co‐design methodology for AI detection of differences between planned and delivered dose in radiotherapy

Journal of Applied Clinical Medical Physics, EarlyView.
Abstract Introduction Many artificial intelligence (AI) solutions have been proposed to enhance the radiotherapy (RT) workflow, but limited applications have been implemented to date, suggesting an implementation gap. One contributing factor to this gap is a misalignment between AI systems and their users.
Luca M. Heising, Frank Verhaegen, Stefan G. Scheib, Maria J. G. Jacobs, Carol X. J. Ou, Viola Mottarella, Yin‐Ho Chong, Mariangela Zamburlini, Sebastiaan M. J. J. G. Nijsten, Ans Swinnen, Michel Öllers, Cecile J. A. Wolfs   +11 more
wiley   +1 more source

Effects of a Personalized Navigation Support Approach on Students’ Context-Aware Ubiquitous Learning Performances

Educational Technology & Society, 2019
In context-aware ubiquitous learning, the learning resources of the learning environment are limited, and the learners need to frequently move between learning targets.
Effects of a Personalized Navigation Support Approach on Students’ Context-Aware Ubiquitous Learning Performances , Chuang-Kai Chiu, Judy C. R. Tseng   +2 more
doaj