Results 61 to 70 of about 603,409 (311)

Applicability of mitotic figure counting by deep learning: a development and pan‐cancer validation study

FEBS Open Bio, EarlyView.
In this study, we developed a deep learning method for mitotic figure counting in H&E‐stained whole‐slide images and evaluated its prognostic impact in 13 external validation cohorts from seven different cancer types. Patients with more mitotic figures per mm2 had significantly worse patient outcome in all the studied cancer types except colorectal ...
Joakim Kalsnes, Maria X. Isaksen, Frida Julbø, Manohar Pradhan, Andreas Kleppe, Sepp De Raedt, Ole‐Johan Skrede, Turid Torheim, John Arne Nesheim, Hans Martin Mohn, Hanne A. Askautrud, Karolina Cyll, Wanja Kildal, Emma Rewcastle, Melinda Lillesand, Vebjørn Kvikstad, Emiel Janssen, Robert Jones, Odd Terje Brustugun, Bjørn Brennhovd, Erik Skaaheim Haug, Lill‐Tove Rasmussen Busund, Elin Richardsen, Sigve Andersen, Tom Dønnem, Kristina Lindemann, Gunnar Kristensen, Neil A. Shepherd, Marco Novelli, Knut Liestøl, David Kerr, Håvard E. Danielsen, Tarjei S. Hveem   +32 more
wiley   +1 more source

Intrinsically Motivated Open-Ended Multi-Task Learning Using Transfer Learning to Discover Task Hierarchy

Applied Sciences, 2021
In open-ended continuous environments, robots need to learn multiple parameterised control tasks in hierarchical reinforcement learning. We hypothesise that the most complex tasks can be learned more easily by transferring knowledge from simpler tasks ...
Nicolas Duminy, Sao Mai Nguyen, Junshuai Zhu, Dominique Duhaut, Jerome Kerdreux   +4 more
doaj   +1 more source

Rapid screening of staphylokinase protein variants using an unpurified cell‐free expression system

FEBS Open Bio, EarlyView.
An unpurified cell‐free protein synthesis (CFPS) platform enables rapid functional screening of staphylokinase variants. Direct plasminogen‐activation assays performed in microplate format provide real‐time activity readouts, allowing rapid identification and ranking of variants with improved or reduced fibrinolytic activity without protein ...
Maria Tomková, Veronika Hovanová, Jiri Damborsky, Erik Sedlák   +3 more
wiley   +1 more source

ConnectomeNet: A Unified Deep Neural Network Modeling Framework for Multi-Task Learning

IEEE Access, 2023
Despite recent advances in deep neural networks (DNNs), multi-task learning has not been able to utilize DNNs thoroughly. The current method of DNN design for a single task requires considerable skill in deciding many architecture parameters a priori ...
Heechul Lim, Kang-Wook Chon, Min-Soo Kim
doaj   +1 more source

Directed evolution of enzymes at the crossroads of tradition and innovation

FEBS Open Bio, EarlyView.
An iterative cycle of data‐driven enzyme optimization comprising four stages: genetic diversification of a template enzyme, expression of protein variants, high‐throughput evaluation, and machine‐learning‐guided redesign of the next variant library.
Maria Tomkova, Andrej Mirossay, Erik Sedlak   +2 more
wiley   +1 more source

Open‐set recognition of compound jamming signal based on multi‐task multi‐label learning

IET Radar, Sonar & Navigation
In the increasingly intricate electromagnetic environment, the radar receiver may simultaneously encounter multiple intentional or unintentional jamming signals, which results in temporal and spectral overlap of received signals and forms a composite ...
Yihan Xiao, Rui Zhang, Xiangzhen Yu, Yilin Jiang   +3 more
doaj   +1 more source

Seeing Pedestrian in the Dark via Multi-Task Feature Fusing-Sharing Learning for Imaging Sensors

Sensors, 2020
Pedestrian detection is an essential problem of computer vision, which has achieved tremendous success under controllable conditions using visible light imaging sensors in recent years.
Yuanzhi Wang, Tao Lu, Tao Zhang, Yuntao Wu   +3 more
doaj   +1 more source

Long‐Term Follow‐Up of Chemotherapy‐Associated Biological Aging in Women With Early Breast Cancer

Aging and Cancer, EarlyView.
Women threated with adjuvant chemotherapy for early breast cancer have sustained long‐term increase in p16INK4a,, a robust marker of cell senescence, suggesting a chemotherapy‐associated age acceleration. p16INK4a as well as other biomarkers may identify patients at greatest risk for senescence‐related diseases of aging.
Hyman B. Muss, Alexis C. Wardell, Allison M. Deal, Kirsten A. Nyrop, Allison Ross, Yara G. Abdou, Jeffrey D. Aldrich, Lisa A. Cary, E. Claire Dees, Katherine E. Reeder‐Hayes, Emily M. Ray, Natalia Mitin, Denis Tsygankov   +12 more
wiley   +1 more source

Multi-Task Multi-Sample Learning [PDF]

, 2015
In the exemplar SVM (E-SVM) approach of Malisiewicz et al., ICCV 2011, an ensemble of SVMs is learnt, with each SVM trained independently using only a single positive sample and all negative samples for the class. In this paper we develop a multi-sample learning (MSL) model which enables joint regularization of the E-SVMs without any additional cost ...
Aytar, Y, Zisserman, A
openaire   +1 more source

Learning feature selection dependencies in multi-task learning [PDF]

, 2013
This is an electronic version of the paper presented at the 27 Annual Conference on Neural Information Processing Systems, held in Lake Tahoe on 2013A probabilistic model based on the horseshoe prior is proposed for learning dependencies in the process ...
Hernández-Lobato, José Miguel, Hernández Lobato, Daniel   +1 more
core