Results 41 to 50 of about 223,210 (262)

Fingerprint Liveness Detection in the Presence of Capable Intruders

Sensors, 2015
Fingerprint liveness detection methods have been developed as an attempt to overcome the vulnerability of fingerprint biometric systems to spoofing attacks. Traditional approaches have been quite optimistic about the behavior of the intruder assuming the
Ana F. Sequeira, Jaime S. Cardoso
doaj   +1 more source

Misperception of Body Weight After Childhood Cancer

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Background Misperception of body weight can negatively impact the weight management efforts of childhood cancer survivors (CCSs). Both being overweight or underweight are associated with chronic health conditions commonly observed in CCS; therefore, accurate weight perception is critical for reducing long‐term health risks.
Fabiën N. Belle, Tomáš Sláma, Eva Haegler‐Laube, Reto D. Kurmann, Gabriela M. Kuster, Christoph Saner, Eva Scheler, Yara Shoman, Christina Schindera   +8 more
wiley   +1 more source

Inpatient Exposure, Confidence, and Knowledge in Pediatric Hematology/Oncology: Evaluating General Pediatric Residents During 2025 ACGME Curriculum Change

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Background General pediatricians often evaluate hematologic and oncologic presentations before subspecialty consultation, yet the 2025 Accreditation Council for Graduate Medical Education (ACGME) pediatric requirements reduce inpatient pediatric hematology/oncology (PHO) time, raising questions about resident readiness.
Colburn Yu, Rohini Jain
wiley   +1 more source

Supervised classification and mathematical optimization [PDF]

Computers & Operations Research, 2013
Data Mining techniques often ask for the resolution of optimization problems. Supervised Classification, and, in particular, Support Vector Machines, can be seen as a paradigmatic instance. In this paper, some links between Mathematical Optimization methods and Supervised Classification are emphasized.
Emilio Carrizosa, Dolores Romero Morales
openaire   +3 more sources

Sociodemographic Factors Associated With Later Stage at Diagnosis of Pediatric Germ Cell Tumors: A Report From Children's Oncology Group Registries ACCRN07 and APEC14B1

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Background Germ cell tumors (GCTs) often arise in the ovaries and testes (extracranial) but can also develop in the brain (intracranial). We examined the relationship of individual, family, and community‐level socioeconomic status (SES) with stage of disease at diagnosis in a cohort of pediatric patients with GCT from Children's Oncology Group
Heydon K. Kaddas, Judy Y. Ou, Todd Alonzo, Logan G. Spector, Negar Fallahazad, Emily Owens, Anne C. Kirchhoff, Adam L. Green   +7 more
wiley   +1 more source

Supervised Classification with Matrix Sketching [PDF]

, 2020
Matrix sketching is a recently developed data compression technique. An input matrix A is efficiently approximated with a smaller matrix B, so that B preserves most of the properties of A up to some guaranteed approximation ratio. In so doing numerical operations on big data sets become faster.
openaire   +2 more sources

Phase Angle as an Early Functional Biomarker of Cancer‐Related Fatigue in Pediatric Oncology: A Prospective Longitudinal Study

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Background Pediatric cancer remains a leading cause of morbidity and mortality worldwide, particularly in low‐and middle‐income countries. Cancer treatment may impair nutritional status, alter body composition, and exacerbate cancer‐related fatigue (CRF).
Luís Carlos Lopes‐Junior, Luiz Claudio Barreto Silva Neto, Fabiano Kenji Haraguchi, Letícia Batista de Azevedo, Marcelo Brenner Nascimento Carlini, Raphael Manhães Pessanha, Mariana Rabello Laignier, Wesley Rocha Grippa, Tania Mara Lopes Bitti Bortolini, Gláucia Zouain‐Figueiredo, Regina Aparecida Garcia de Lima, Liliana Vasquez   +11 more
wiley   +1 more source

MalSSL—Self-Supervised Learning for Accurate and Label-Efficient Malware Classification

IEEE Access
Malware classification with supervised learning requires a large dataset, which needs an expensive and time-consuming labeling process. In this paper, we explore the efficacy of self-supervised learning techniques for malware classification.
Setia Juli Irzal Ismail, Hendrawan, Budi Rahardjo, Tutun Juhana, Yasuo Musashi   +4 more
doaj   +1 more source

Effectiveness of Semi-Supervised Learning and Multi-Source Data in Detailed Urban Landuse Mapping with a Few Labeled Samples

Remote Sensing, 2022
Detailed urban landuse information plays a fundamental role in smart city management. A sufficient sample size has been identified as a very crucial pre-request in machine learning algorithms for urban landuse classification.
Bo Sun, Yang Zhang, Qiming Zhou, Xinchang Zhang   +3 more
doaj   +1 more source

Mapping Childhood Cancer Care Services in Oceania: Methodological Lessons From the SIOP Global Mapping Programme

Pediatric Blood &Cancer, EarlyView.
ABSTRACT The International Paediatric Oncology Society Global Mapping Programme aims to collect data on global paediatric oncology services by continent, with Africa and Latin America completed. This study reports on the methodology and lessons learned for Oceania, a unique continent with resource disparity across countries, multiple small island ...
Trisha Soosay Raj, Christy Noble, Amy Gray, Daniel C. Moreira, Jennifer Lowe, Maite Gorostegui, Gwenda Anga, Andrew Soma, Milena Lay Dos Santos, Siobhan Cross, Erin Luttrell, Michael Sullivan, Julie Cayrol, Julia Challinor, Neil Ranasinghe, Jordana McLoone, Claire E. Wakefield   +16 more
wiley   +1 more source