Results 61 to 70 of about 1,352,011 (292)

An Artificial Neural Network Approach for Solving Inverse Kinematics Problem for an Anthropomorphic Manipulator of Robot SAR-401

Machines, 2022
The paper proposes a new design of an artificial neural network for solving the inverse kinematics problem of the anthropomorphic manipulator of robot SAR-401.
Vadim Kramar, Oleg Kramar, Aleksey Kabanov   +2 more
doaj   +1 more source

Concordance measure and discriminatory accuracy in transformation cure models [PDF]

Biostatistics, 2017
Many populations of early-stage cancer patients have non-negligible latent cure fractions that can be modeled using transformation cure models. However, there is a lack of statistical metrics to evaluate prognostic utility of biomarkers in this context due to the challenges associated with unknown cure status and heavy censorship.
Yilong, Zhang, Yongzhao, Shao
openaire   +2 more sources

Recurrent Saliency Transformation Network: Incorporating Multi-Stage Visual Cues for Small Organ Segmentation

, 2018
We aim at segmenting small organs (e.g., the pancreas) from abdominal CT scans. As the target often occupies a relatively small region in the input image, deep neural networks can be easily confused by the complex and variable background.
Fishman, Elliot K., Wang, Yan, Xie, Lingxi, Yu, Qihang, Yuille, Alan L., Zhou, Yuyin   +5 more
core   +1 more source

Subtype‐specific enhancer RNAs define transcriptional regulators and prognosis in breast cancers

Molecular Oncology, EarlyView.
This study employed machine learning methodologies to perform the subtype‐specific classification of RNA‐seq data sets, which are mapped on enhancers from TCGA‐derived breast cancer patients. Their integration with gene expression (referred to as ProxCReAM eRNAs) and chromatin accessibility profiles has the potential to identify lineage‐specific and ...
Aamena Y. Patel, Peyman Zarrineh, Nathnael T. Tuffa, Jigar H. Sheth, Sumitra Mohan, Mudassar Iqbal, Sankari Nagarajan   +6 more
wiley   +1 more source

Meta-Learning for Phonemic Annotation of Corpora [PDF]

, 2000
We apply rule induction, classifier combination and meta-learning (stacked classifiers) to the problem of bootstrapping high accuracy automatic annotation of corpora with pronunciation information. The task we address in this paper consists of generating
Daelemans, W., Gillis, S., Hoste, V., Tjong Kim Sang, E.F., van den Bosch, A., Weigand, H.   +5 more
core   +9 more sources

Cell‐cycle‐specific lesion evolution rather than inhibition of double‐strand‐break repair underpins cisplatin radiosensitization

Molecular Oncology, EarlyView.
We analyze cisplatin–DNA adducts (CDAs) and double‐strand breaks (DSBs) in a cell‐cycle‐dependent manner. We find that CDAs form similarly across all cell cycle phases. DSBs arise only in S‐phase. CDAs might not directly impair DSB repair, but S‐phase DSB lesions evolve in the presence of CDAs and disrupt repair in G2, also causing radiosensitization ...
Ye Qiu, Xixi Lin, Emil Mladenov, Veronika Mladenova, Jürgen Thomale, Ali Sak, Yao Wang, Yunxuan Deng, Eleni Gkika, Martin Stuschke, George Iliakis   +10 more
wiley   +1 more source

Molecular cancer prevention: Intercepting disease

Molecular Oncology, EarlyView.
Oncological practice must evolve, from treating established tumours to proactive cancer interception before clinical manifestation. This will require mechanistic insight into tumour initiation, validated biomarkers of early disease development and redesigned clinical trials, enabling cancer interception to become a core pillar of oncology with the ...
Charlotte Grieco, Tej Pandya, Charles Swanton   +2 more
wiley   +1 more source

Development of Steady Aiming System Based on Kalman Filter and Coordinate Transformation

IEEE Access, 2023
The aiming accuracy of the Unmanned Aerial Vehicles (UAV) Steadicam head can be affected by many factors, such as the state of the UAV during the actual flight and the installation error of the system related hardware. In order to eliminate the influence
Yufang Lu, Lisha Meng, Haihua Tang, Lei Shi   +3 more
doaj   +1 more source

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

Analysing the significance of small conformational changes and low occupancy states in serial crystallographic data

FEBS Open Bio, EarlyView.
This protocol paper outlines methods to establish the success of a time‐resolved serial crystallographic experiment, by means of statistical analysis of timepoint data in reciprocal space and models in real space. We show how to amplify the signal from excited states to visualise structural changes in successful experiments.
Jake Hill, Yelyzaveta Pulnova, Elke De Zitter, Helen M. Ginn, Briony A. Yorke   +4 more
wiley   +1 more source