Results 61 to 70 of about 1,818,152 (349)

A New Interpretable Unsupervised Anomaly Detection Method Based on Residual Explanation

IEEE Access, 2022
Despite the superior performance in modeling complex patterns to address challenging problems, the black-box nature of Deep Learning (DL) methods impose limitations to their application in real-world critical domains.
David F. N. Oliveira, Lucio F. Vismari, Alexandre M. Nascimento, Jorge R. de Almeida, Paulo S. Cugnasca, Joao B. Camargo, Leandro Almeida, Rafael Gripp, Marcelo Neves   +8 more
doaj   +1 more source

Inverse Classification for Comparison-based Interpretability in Machine Learning

, 2017
In the context of post-hoc interpretability, this paper addresses the task of explaining the prediction of a classifier, considering the case where no information is available, neither on the classifier itself, nor on the processed data (neither the ...
A Watson, D Baehrens, D Martens, E Štrumbelj, JD Tygar, JM Alonso, K Fernandes, LA Hendricks, M Gacto, MV Mannino, N Mvududu, R Harman, T Gog van, Y LeCun   +13 more
core   +1 more source

Nutritional and Behavioral Intervention for Long‐Term Childhood Acute Leukemia Survivors With Metabolic Syndrome

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Purpose Metabolic syndrome (MetS) is a common complication in survivors of childhood acute lymphoblastic and myeloid leukemia (AL), and a major risk factor for premature cardiovascular disease, type‐2‐diabetes, and metabolic dysfunction‐associated steatotic liver disease (MASLD).
Visentin Sandrine, Béliard Sophie, Renard Cécile, Caussy Cyrielle, Hamidou Zeinab, Romano David, Gacem Mélanie, Petit Arnaud, Saultier Paul, Borentain Patrick, Michel Gérard   +10 more
wiley   +1 more source

Emulating quantum dynamics with neural networks via knowledge distillation

Frontiers in Materials, 2023
We introduce an efficient training framework for constructing machine learning-based emulators and demonstrate its capability by training an artificial neural network to predict the time evolution of quantum wave packets propagating through a potential ...
Yu Yao, Chao Cao, Stephan Haas, Mahak Agarwal, Divyam Khanna, Marcin Abram, Marcin Abram   +6 more
doaj   +1 more source

SPINE: SParse Interpretable Neural Embeddings

, 2017
Prediction without justification has limited utility. Much of the success of neural models can be attributed to their ability to learn rich, dense and expressive representations.
Berg-Kirkpatrick, Taylor, Hovy, Eduard, Jhamtani, Harsh, Pruthi, Danish, Subramanian, Anant   +4 more
core   +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

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

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

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

Lithium-Ion Battery Health Assessment Method Based on Double Optimization Belief Rule Base with Interpretability

Batteries
Health assessment is necessary to ensure that lithium-ion batteries operate safely and dependably. Nonetheless, there are the following two common problems with the health assessment models for lithium-ion batteries that are currently in use: inability ...
Zeyang Si, Jinting Shen, Wei He
doaj   +1 more source