Results 81 to 90 of about 101,283 (263)

Encoding local label correlations in multi-instance multi-label learning with an improved multi-objective particle swarm optimization

Complex & Intelligent Systems
Label correlations, as important prior information, are essential to enhance the classification performance in Multi-Instance Multi-Label (MIML) algorithms, but existing models always leverage global label correlations which are less informative ...
Xiang Bao, Fei Han, Qinghua Ling
doaj   +1 more source

Keratin 19 as a prognostic marker and contributing factor of metastasis and chemoresistance in high‐grade serous ovarian cancer

Molecular Oncology, EarlyView.
Keratin 19 (KRT19) is overexpressed in high‐grade serous ovarian cancer with high levels of Kallikrein‐related peptidases (KLK) 4–7 and is associated with poor survival. In vivo analyses demonstrate that elevated KRT19 increases peritoneal tumour burden.
Sophia Bielesch, Isabel Vogel, Sina Nokodian, Johanna Moeller, Antonia Blechschmidt, Vicky Hecht, Vanessa Kuentzel, Katharina Thiedig, Melissa Schwab, Oliver Schilling, Holger Bronger, Marion Kiechle, Viktor Magdolen, Tobias Dreyer   +13 more
wiley   +1 more source

Embedded EEG Feature Selection for Multi-Dimension Emotion Recognition via Local and Global Label Relevance

IEEE Transactions on Neural Systems and Rehabilitation Engineering
Due to the problem of a small amount of EEG samples and relatively high dimensionality of electroencephalogram (EEG) features, feature selection plays an essential role in EEG-based emotion recognition.
Xueyuan Xu, Fulin Wei, Tianyuan Jia, Li Zhuo, Hui Zhang, Xiaoguang Li, Xia Wu   +6 more
doaj   +1 more source

Establishment of a humanized patient‐derived xenograft mouse model of high‐grade serous ovarian cancer for preclinical evaluation of combination immunotherapy

Molecular Oncology, EarlyView.
We have established a humanized orthotopic patient‐derived xenograft (Hu‐oPDX) mouse model of high‐grade serous ovarian cancer (HGSOC) that recapitulates human tumor–immune interactions. Using combined anti‐PD‐L1/anti‐CD73 immunotherapy, we demonstrate the model's improved biological relevance and enhanced translational value for preclinical ...
Luka Tandaric, Line Bjørge, Martine Rott Lode, Cecilie Fredvik Torkildsen, Pia Aehnlich, Rammah Elnour, Daniela Elena Costea, Lars Andreas Akslen, Liv Cecilie Vestrheim Thomsen, Emmet McCormack, Katrin Kleinmanns   +10 more
wiley   +1 more source

Multi-label feature selection via label orthogonal embedding and feature self-representation

Journal of King Saud University: Computer and Information Sciences
In multi-label applications like text classification, feature selection is crucial for reducing complexity and enhancing interpretability. Existing methods often inadequately exploit label space discriminative information and rely excessively on pairwise
Xiaoxia Wang, Shuisheng Zhou, Binjie Hou, Shuai Zhao   +3 more
doaj   +1 more source

Prompt-Based Label-Aware Framework for Few-Shot Multi-Label Text Classification

IEEE Access
Prompt-based learning has demonstrated remarkable success in few-shot text classification, outperforming the traditional fine-tuning approach. This method transforms a text input into a masked language modeling prompt using a template, queries a fine ...
Thanakorn Thaminkaew, Piyawat Lertvittayakumjorn, Peerapon Vateekul   +2 more
doaj   +1 more source

Differential expression of cancer‐related genes supports prediction of poor response to first‐line treatments in T‐ALL pediatric patients with high minimal residual disease

Molecular Oncology, EarlyView.
In the present work, we have identified a transcriptional signature based on the differential expression of six genes (BCL2&MAST4, HSH2D&LAT2, METRN&PITPNM2) that would facilitate the early detection of T‐cell acute lymphoblastic leukemia (T‐ALL) patients prone to a poor treatment response and could be implemented at diagnosis, along with other risk ...
Antonio Lahera, Laura Vela‐Martín, Pablo Fernández‐Navarro, José Luis López‐Lorenzo, Javier Cornago, Pilar Llamas, Eduardo Pérez‐Gómez, José Luis Marín‐Rubio, Manuel Fresno, Javier Santos, José Fernández‐Piqueras, María Villa‐Morales   +11 more
wiley   +1 more source

Label-aware debiased causal reasoning for Natural Language Inference

AI Open
Recently, researchers have argued that the impressive performance of Natural Language Inference (NLI) models is highly due to the spurious correlations existing in training data, which makes models vulnerable and poorly generalized.
Kun Zhang, Dacao Zhang, Le Wu, Richang Hong, Ye Zhao, Meng Wang   +5 more
doaj   +1 more source

CCDC80 suppresses high‐grade serous ovarian cancer migration via negative regulation of B7‐H3

Molecular Oncology, EarlyView.
PAX8 is a lineage‐specific master regulator of transcription in high‐grade serous ovarian cancer (HGSC) progression. We show for the first time that PAX8 facilitates proliferation and metastasis by repressing the cell autonomous tumor suppressor CCDC80 and inducing B7‐H3 expression.
Aya Saleh, Nitzan Medina‐Itzhaki, Milena Chekov, Eden Gal‐Swisa, Roba Gabesh‐Wahabi, Inbar Savyon, Inna Naroditsky, Hilary A. Kenny, Basem Fares, Lina Korsensky, Einav Girsh, Liron Berger, Ruth Perets   +12 more
wiley   +1 more source

KDM7A and KDM1A inhibition suppresses tumour promoting pathways in prostate cancer

Molecular Oncology, EarlyView.
Treatment resistance is a major challenge for patients with advanced prostate cancer. This study examined an alternative approach to target the major prostate cancer‐promoting pathway by targeting epigenetic factors, whose levels are higher in tumours.
Jennie N Jeyapalan, Veronika M Metzler, Simone de Brot, Corinne L Woodcock, Anna E Harris, Jennifer Lothion‐Roy, Emeli M Nilsson, Atara Ntekim, Michael S Toss, Jenny L Persson, Francesca Khani, Brian D Robinson, Lorraine J Gudas, Emad Rakha, David M Heery, Catrin S Rutland, Nigel P Mongan   +16 more
wiley   +1 more source