Results 81 to 90 of about 7,571,754 (304)

Regularized partial least squares for multi-label learning

, 2016
In reality, data objects often belong to several different categories simultaneously, which are semantically correlated to each other. Multi-label learning can handle and extract useful information from such kind of data effectively. Since it has a great
Chen, Zhongyu, Zongjie Ma, Han, Jianmin, Jianmin Han, Zhonglong Zheng, Liu, Huawen, Huawen Liu, Zhongyu Chen, Zheng, Zhonglong, Ma, Zongjie   +9 more
core   +1 more source

Incomplete multi–view partial multi–label learning network with structure–aware consistent fusion

Journal of King Saud University: Computer and Information Sciences
In recent years, incomplete multi-view partial multi-label classification has attracted growing attention due to its practical relevance. However, many existing methods rely on equal-weight (average) fusion and thus overlook sample-wise reliability ...
Xingang Mao, Yang Xu, Wenbin Bu, Zherui Yang   +3 more
doaj   +1 more source

Multi-Label Feature Selection Based on High-Order Label Correlation Assumption

Entropy, 2020
Multi-label data often involve features with high dimensionality and complicated label correlations, resulting in a great challenge for multi-label learning.
Ping Zhang, Wanfu Gao, Juncheng Hu, Yonghao Li   +3 more
doaj   +1 more source

Risk Prediction Models for Recurrence After Curative Treatment of Early‐Stage or Locally Advanced Lung Cancer: A Systematic Review

Aging and Cancer, EarlyView.
This systematic review synthesizes prognostic models for survival and recurrence in resected non‐small cell lung cancer. While many models demonstrate moderate to good discrimination, few are externally validated and reporting quality is variable, limiting clinical applicability and highlighting the need for robust, transparent model development ...
Evangeline Samuel, S. Tissera, E. Paul, J. Zalcberg, R. G. Stirling   +4 more
wiley   +1 more source

Developmental and Epileptic Encephalopathy due to Biallelic Pathogenic Variants in PIGM

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective PIGM encodes a critical enzyme in the glycosylphosphatidylinositol (GPI)‐anchor biosynthesis pathway. While promoter‐region mutations in PIGM have been associated with a relatively mild phenotype characterized by portal vein thrombosis and absence seizures, recent evidence suggests that coding‐region mutations result in a more severe
Júlia Sala‐Coromina, Anna Marcé‐Grau, Barbara Masotto, Marta Codina, Lamia BenJemaa, Yasmina Elaribi, Mónica Martinez‐Gallo, Roger Colobran, Angel Sanchez‐Montañez, Irene Valenzuela, Yoshiko Murakami, Alfons Macaya   +11 more
wiley   +1 more source

Semantically Guided Multi-Stage Graph Learning for Inductive Multi-Label Text Classification

Journal of King Saud University: Computer and Information Sciences
Most graph neural network-based multi-label text classification methods suffer from two key engineering limitations: poor generalization to unseen data due to transductive learning, and suboptimal performance caused by fixed-label graphs that fail to ...
Mingqiang Wu
doaj   +1 more source

Local Rademacher Complexity for Multi-Label Learning [PDF]

IEEE Transactions on Image Processing, 2016
We analyze the local Rademacher complexity of empirical risk minimization (ERM)-based multi-label learning algorithms, and in doing so propose a new algorithm for multi-label learning. Rather than using the trace norm to regularize the multi-label predictor, we instead minimize the tail sum of the singular values of the predictor in multi-label ...
Chang Xu 0002, Tongliang Liu, Dacheng Tao, Chao Xu 0006   +3 more
openaire   +3 more sources

Longitudinal Assessment of Biomarkers in ALS: Discriminative Biomarkers for Disease Progression and Survival

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To assess the association and discriminative performance of serum biomarkers with clinical disease progression and survival in patients with amyotrophic lateral sclerosis (ALS). Methods This retrospective study, conducted at Houston Methodist Hospital, Houston, TX, used longitudinal serum samples collected between January 2018 and ...
David R. Beers, Yueh‐Yun Lin, Jason R. Thonhoff, Aaron D. Thome, Alireza Faridar, Weihua Zhao, Shixiang Wen, Stanley H. Appel   +7 more
wiley   +1 more source

Adversarial Partial Multi-Label Learning with Label Disambiguation

, 2021
Partial multi-label learning (PML), which tackles the problem of learning multi-label prediction models from instances with overcomplete noisy annotations, has recently started gaining attention from the research community.
Guo, Yuhong, Yan, Yan
core   +1 more source

Screening Routine Clinical Notes for Epilepsy Surgery Candidates Using Large Language Models

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Epilepsy surgery is severely underutilized despite proven efficacy, with substantial under‐referral of eligible patients in routine clinical practice. This study evaluated the potential role of large language models (LLMs) as decision‐support tools for screening unstructured clinical notes to identify epilepsy surgery candidates and ...
Uriel Fennig, Nadav Amir, Maya Schiller, Roni Loebenstein, Johnatan Nissan, Marina Boxer, Shany Guly Gofrit, Gal Goshen, Sándor Beniczky, Nicola Maggio   +9 more
wiley   +1 more source