Results 31 to 40 of about 1,216,046 (262)

Artificial intelligence applications in cardio-oncology: Leveraging high dimensional cardiovascular data

Frontiers in Cardiovascular Medicine, 2022
Growing evidence suggests a wide spectrum of potential cardiovascular complications following cancer therapies, leading to an urgent need for better risk-stratifying and disease screening in patients undergoing oncological treatment.
Haidee Chen, David Ouyang, Tina Baykaner, Faizi Jamal, Paul Cheng, June-Wha Rhee   +5 more
doaj   +1 more source

Finding k-Dominant G-Skyline Groups on High Dimensional Data

IEEE Access, 2018
Skyline query retrieves a set of skyline points which are not dominated by any other point and has attracted wide attention in database community. Recently, an important variant G-Skyline is developed. It aims to return optimal groups of points. However,
Kaiqi Zhang, Hong Gao, Xixian Han, Jinbao Wang   +3 more
doaj   +1 more source

A classification method for high‐dimensional imbalanced multi‐classification data

Electronics Letters, 2023
High‐dimensional imbalanced multi‐classification problems (HDIMCPs) occur frequently in engineering applications such as medical detection, item classification, and email classification.
Mengmeng Li, Qibin Zheng, Yi Liu, Gengsong Li, Wei Qin, Xiaoguang Ren   +5 more
doaj   +1 more source

Feature Selection in High Dimensional Biomedical Data Based on BF-SFLA

Frontiers in Neuroscience, 2022
High-dimensional biomedical data contained many irrelevant or weakly correlated features, which affected the efficiency of disease diagnosis. This manuscript presented a feature selection method for high-dimensional biomedical data based on the ...
Yongqiang Dai, Lili Niu, Linjing Wei, Jie Tang   +3 more
doaj   +1 more source

Longitudinal study of infants born preterm (

BMJ Open
Purpose The SEV-IDF programme aims to track infants born before 33 weeks of gestation, with very low birth weight (VLBW), neonatal encephalopathy or severe birth anomalies and perinatal disease.
Michèle Granier, Véronique Zupan-Simunek, Pascale Tubert‐Bitter, Alexandre Lapillonne, Matthieu Hanf, Audrey Rolland, Cécile Lebeaux, Lucas Anzelin, Anne C M Thiébaut, Laurence Leloup, Sylvie Escolano, Laurence Desplanques, SEV-IDF study group, Laureline Mathieu, Manuela Briand, Michèle Manière, Simona Sermasi, Nadia Medejel   +17 more
doaj   +1 more source

Learning to visualise high-dimensional data [PDF]

Proceedings. Eighth International Conference on Information Visualisation, 2004. IV 2004., 2004
Visualisation techniques focus on reducing high dimensional data to a low dimensional surface or a cube. Similar dimensional reduction is attempted in the so-called 'self-organising maps'. A number of techniques have been developed to visualise categories learnt by these maps through and exemplified by the term sequential clustering.
Ahmad, Khurshid, Vrusias, Bogdan
openaire   +2 more sources

Clustering Evaluation in High-Dimensional Data [PDF]

, 2016
Clustering evaluation plays an important role in unsupervised learning systems, as it is often necessary to automatically quantify the quality of generated cluster configurations. This is especially useful for comparing the performance of different clustering algorithms as well as determining the optimal number of clusters in clustering algorithms that
Nenad Tomašev, Miloš Radovanović
openaire   +2 more sources

An efficient predictive analytics system for high dimensional big data

Journal of King Saud University: Computer and Information Sciences, 2022
The excessive growth of high dimensional big data has resulted in a greater challenge for data scientists to efficiently obtain valuable knowledge from these data. Traditional data mining techniques are not fit to process big data.
Myat Cho Mon Oo, Thandar Thein
doaj   +1 more source

Evidence‐Informed Multidisciplinary Consensus Guidance for the Psychosocial Care of Adolescents With High‐Risk Cancer: Recommendations From the Italian Association of Pediatric Hematology and Oncology

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Background Adolescents with high‐risk cancer face complex developmental, psychosocial, and ethical challenges that extend beyond disease‐directed treatment. Although international recommendations exist for communication, psychosocial care, pediatric palliative care, survivorship, and shared decision‐making, these have largely evolved within ...
Johanna M. C. Blom, Dorella Scarponi, Giulia Zucchetti, Teresa Perillo, Maria Montanaro, Elisa Marconi, Chiara Rutigliano, Paolo Colavero, Paola Quarello, Marina Bertolotti, Monica Cellini, Carlo Clerici, Maurizio Mascarin, Francesca Bomben, Andrea Ferrari, the expert workgroup   +15 more
wiley   +1 more source

FCM classifier for high-dimensional data [PDF]

2008 IEEE International Conference on Fuzzy Systems (IEEE World Congress on Computational Intelligence), 2008
A fuzzy classifier based on the fuzzy c-means (FCM) clustering has shown a decisive generalization ability in classification. The FCM classifier uses covariance structures to represent flexible shapes of clusters. Despite its effectiveness, the intense computation of covariance matrices is an impediment for classifying a set of high-dimensional data ...
Hidetomo Ichihashi, Katsuhiro Honda, Akira Notsu, Eri Miyamoto   +3 more
openaire   +2 more sources