Results 31 to 40 of about 2,455,864 (308)

Self-supervised learning for remote sensing scene classification under the few shot scenario

Scientific Reports, 2023
Scene classification is a crucial research problem in remote sensing (RS) that has attracted many researchers recently. It has many challenges due to multiple issues, such as: the complexity of remote sensing scenes, the classes overlapping (as a scene ...
Najd Alosaimi, Haikel Alhichri, Yakoub Bazi, Belgacem Ben Youssef, Naif Alajlan   +4 more
doaj   +1 more source

Changes in Body Composition in Children and Young People Undergoing Treatment for Acute Lymphoblastic Leukemia: A Systematic Review and Meta‐Analysis

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Ongoing evidence indicates increased risk of sarcopenic obesity among children and young people (CYP) with acute lymphoblastic leukemia (ALL), often beginning early in treatment, persisting into survivorship. This review evaluates current literature on body composition in CYP with ALL during and after treatment.
Lina A. Zahed, Raquel Revuelta Iniesta, Mary Fewtrell, Julie Lanigan, Breeana Gardiner, Graeme O'Connor   +5 more
wiley   +1 more source

Using machine learning to identify frequent attendance at accident and emergency services in Lanarkshire

Digital Health
Background Frequent attenders to accident and emergency (A&E) services pose complex challenges for healthcare providers, often driven by critical clinical needs.
Fergus Reid, S. Josephine Pravinkumar, Roma Maguire, Ashleigh Main, Haruno McCartney, Lewis Winters, Feng Dong   +6 more
doaj   +1 more source

Parent‐to‐Child Information Disclosure in Pediatric Oncology

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Background Despite professional consensus regarding the importance of open communication with pediatric cancer patients about their disease, actual practice patterns of disclosure are understudied. Extant literature suggests a significant proportion of children are not told about their diagnosis/prognosis, which is purported to negatively ...
Rachel A. Kentor, Flora Hoodin, Michelle Byrd, Kristin A. Kullgren, Leah LaLonde, Lauren Benkoske, Patrick Smith, Dawn Carson, Karen MacDonald, Susumu Inoue, Brenda Kitchen, Kate Gowans, Gregory A. Yanik   +12 more
wiley   +1 more source

Radiotherapy Delivery in Deep Inspiration for Pediatric Patients—Final Results of the Phase II Feasibility Study TEDDI

Pediatric Blood &Cancer, EarlyView.
Abstract Introduction The TEDDI trial tested the feasibility and reproducibility of deep‐inspiration breath‐hold (DIBH) in pediatric patients referred for radiotherapy. This report presents final results, including patient‐reported outcomes (PRO) and dosimetric comparison of DIBH and free‐breathing (FB).
Daniella Elisabet Østergaard, Anni Young Lundgaard, Laura Ann Rechner, Danijela Dejanovic, Hanne Krogh Rose, Jolanta Hansen, Leila Vaalavirta, Miia Mokka, Marianne Aznar, Peder Skov Wehner, Lisa Lyngsie Hjalgrim, Maja Vestmø Maraldo   +11 more
wiley   +1 more source

Study of the Self-archival Pattern Among Iranian Authors: A Comparison Between the Scopes of Science and Social Sciences [PDF]

تحقیقات اطلاع‌رسانی و کتابخانه‌های عمومی, 2011
Purpose: This research is devoted to find out the level of self-archival pattern among Iranian researchers with high rate of publications, based upon the ISI citation indices in the scopes of science and social sciences.
Farkhondeh Ojagh, Keyvan Koosha
doaj  

Prolonged Corrected QT Interval as an Early Electrocardiographic Marker of Cyclophosphamide‐Induced Cardiotoxicity in Pediatric Hematology and Oncology Patients

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Background Cyclophosphamide (CY) is associated with potentially fatal cardiotoxicity, yet no electrocardiographic indices have been established for early detection of CY‐induced cardiomyopathy. This study aimed to determine whether corrected QT interval (QTc) prolongation can predict early onset of CY‐related cardiac dysfunction in pediatric ...
Junpei Kawamura, Kentaro Ueno, Takuro Nishikawa, Yoshihiro Takahashi, Koji Nakae, Yasuhiro Okamoto   +5 more
wiley   +1 more source

Predicting Chronicity in Children and Adolescents With Newly Diagnosed Immune Thrombocytopenia at the Timepoint of Diagnosis Using Machine Learning‐Based Approaches

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Objectives To identify predictors of chronic ITP (cITP) and to develop a model based on several machine learning (ML) methods to estimate the individual risk of chronicity at the timepoint of diagnosis. Methods We analyzed a longitudinal cohort of 944 children enrolled in the Intercontinental Cooperative immune thrombocytopenia (ITP) Study ...
Severin Kasser, Alice Bizeul, Meera Chitlur, Hugo Donato, Jelena Roganovic, Julia E. Vogt, Thomas Kühne   +6 more
wiley   +1 more source

Admissions in the age of AI: detecting AI-generated application materials in higher education

Scientific Reports
Recent advances in Artificial Intelligence (AI), such as the development of large language models like ChatGPT, have blurred the boundaries between human and AI-generated text. This has led to a pressing need for tools that can determine whether text has
Yijun Zhao, Alexander Borelli, Fernando Martinez, Haoran Xue, Gary M. Weiss   +4 more
doaj   +1 more source

A Systematic Review of Evidence on the Clinical Effectiveness of Surveillance Imaging in Children With Medulloblastoma and Ependymoma

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Surveillance imaging aims to detect tumour relapse before symptoms develop, but it's unclear whether earlier detection of relapse leads to better outcomes in children and young people (CYP) with medulloblastoma and ependymoma. This systematic review aims to identify relevant literature to determine the efficacy of surveillance magnetic ...
Lucy Shepherd, Melissa Taylor, Helen Fulbright, Bob Phillips   +3 more
wiley   +1 more source