Results 51 to 60 of about 92,800 (264)

NiaAutoARM: Automated Framework for Constructing and Evaluating Association Rule Mining Pipelines

Mathematics
Numerical Association Rule Mining (NARM), which simultaneously handles both numerical and categorical attributes, is a powerful approach for uncovering meaningful associations in heterogeneous datasets.
Uroš Mlakar, Iztok Fister, Iztok Fister
doaj   +1 more source

Prediction of contraceptive discontinuation among reproductive-age women in Ethiopia using Ethiopian Demographic and Health Survey 2016 Dataset: A Machine Learning Approach

BMC Medical Informatics and Decision Making, 2023
Background Globally, 38% of contraceptive users discontinue the use of a method within the first twelve months. In Ethiopia, about 35% of contraceptive users also discontinue within twelve months.
Shimels Derso Kebede, Yakub Sebastian, Abraham Yeneneh, Ashenafi Fentahun Chanie, Mequannent Sharew Melaku, Agmasie Damtew Walle   +5 more
doaj   +1 more source

Patient therapy outcome modeling in cancer organoids is improved by cancer‐associated fibroblasts and organoid assembly convolution

Molecular Oncology, EarlyView.
Patient‐derived organoids (PDOs) from pancreatic, colorectal, and gastric cancers were used to evaluate standard and experimental therapies. Incorporating cancer‐associated fibroblasts (CAFs) into organoid cultures improved patient therapy outcome prediction.
Marcin Grochowski, Liudmyla Dolinchuk, Michał Jerzak, Albert Gandurski, Tomasz Grochowski, Weronika Wojtyś, Maciej Zadrożny, Wojciech Kaźmierczak, Małgorzata Lenarcik, Marta Matejak‐Górska, Radosław Samsel, Tomasz Olesiński, Dawid Walerych   +12 more
wiley   +1 more source

Online Multiple Object Tracking Using Rule Distillated Siamese Random Forest

IEEE Access, 2020
In a multiple object tracking (MOT) system, an association check between the tracker and detected objects is an important factor in determining the tracking performance. Siamese convolution neural network (CNN) is the most popular data association method
Jimi Lee, Sangwon Kim, Byoung Chul Ko
doaj   +1 more source

Epigenetic heterogeneity and plasticity in therapy‐induced tumor states through single‐cell multi‐omics

Molecular Oncology, EarlyView.
Single‐cell multi‐omics reveals epigenetic heterogeneity across therapy‐adaptive tumor states, including quiescent/dormant, drug‐tolerant persister, and EMT‐like phenotypes. By linking regulatory features with state‐associated biomarkers, these approaches inform biomarker‐guided therapeutic strategies for evolving tumors.
Hee Jung Kim, Hwiyeong Lee, Jin Hong, Daechan Park   +3 more
wiley   +1 more source

Mining GO annotations for improving annotation consistency. [PDF]

PLoS ONE, 2012
Despite the structure and objectivity provided by the Gene Ontology (GO), the annotation of proteins is a complex task that is subject to errors and inconsistencies.
Daniel Faria, Andreas Schlicker, Catia Pesquita, Hugo Bastos, António E N Ferreira, Mario Albrecht, André O Falcão   +6 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

Large‐scale bidirectional arrayed genetic screens identify OXR1 and EMC4 as modifiers of αSynuclein aggregation

FEBS Open Bio, EarlyView.
Activation of the mitochondrial protein OXR1 increases pSyn129 αSynuclein aggregation by lowering ATP levels and altering mitochondrial membrane potential, particularly in response to MSA‐derived fibrils. In contrast, ablation of the ER protein EMC4 enhances autophagic flux and lysosomal clearance, broadly reducing α‐synuclein aggregates.
Sandesh Neupane, Lea Nikolić, Lorenzo Maraio, Thomas Goiran, Nathan Karpilovsky, Stefano Sellitto, Vangelis Bouris, Jiang‐An Yin, Ronald Melki, Edward A Fon, Adriano Aguzzi, Elena De Cecco   +11 more
wiley   +1 more source

Deep Learning-Based Reasoning With Multi-Ontology for IoT Applications

IEEE Access, 2019
In the era of mobile big data, data driven intelligent Internet of Things (IoT) applications are becoming widespread, and knowledge-based reasoning is one of the essential tasks of these applications.
Jin Liu, Xin Zhang, Yunhui Li, Jin Wang, Hye-Jin Kim   +4 more
doaj   +1 more source

Horizontal Learning Approach to Discover Association Rules

Computers
Association rule learning is a machine learning approach aiming to find substantial relations among attributes within one or more datasets. We address the main problem of this technology, which is the excessive computation time and the memory requirements needed for the processing of discovering the association rules.
Arthur Yosef, Idan Roth, Eli Shnaider, Amos Baranes, Moti Schneider   +4 more
openaire   +2 more sources