Results 31 to 40 of about 1,218,748 (261)
Regularized Sparse Modelling for Microarray Missing Value Estimation
The existence of missing values in microarray data inevitably hinders downstream biological analyses that expect complete data as input, therefore how to effectively explore the underlying structure of data to accurately estimate missing entries remains ...
Aiguo Wang, Jing Yang, Ning An
doaj +1 more source
Solid Pseudopapillary Neoplasm of the Pancreas in Children and Adolescents: Expert Recommendations
ABSTRACT Solid pseudopapillary neoplasm of the pancreas (SPN) is a rare low‐grade malignant exocrine pancreatic tumor, mostly discovered during the second decade of life in females, with a very good prognosis, provided microscopically complete surgical excision is achieved.
Sabine Irtan +18 more
wiley +1 more source
ABSTRACT As part of the European Cooperative Study Group for Paediatric Rare Tumours initiative, we developed standard clinical practice guidelines for ovarian sex cord stromal tumors, based on comprehensive national and international cohort analyses, literature review, and a final expert consensus conference.
Dominik T. Schneider +15 more
wiley +1 more source
A New Method for Handling Large Missing Values from Rain Gauge Sensors
Many Internet of Things (IoT)-based systems transmit data quickly in a short time. Unfortunately, not all IoT devices transmit complete sensor data, resulting in data loss, which is a common problem faced by IoT-based systems.
Ikke Dian Oktaviani +3 more
doaj +1 more source
Missing Value Imputation Methods for Electronic Health Records
Electronic health records (EHR) are patient-level information, e.g., laboratory tests and questionnaires, stored in electronic format. Compared to physical records, the EHR alternative allows patients to access their data easily and helps staff with ...
Konstantinos Psychogyios +3 more
doaj +1 more source
Conformal Prediction with Missing Values
Conformal prediction is a theoretically grounded framework for constructing predictive intervals. We study conformal prediction with missing values in the covariates -- a setting that brings new challenges to uncertainty quantification. We first show that the marginal coverage guarantee of conformal prediction holds on imputed data for any missingness ...
Zaffran, Margaux +3 more
openaire +4 more sources
Acute Neurological Events in Children With Hemoglobin SC Disease: A Multicenter Retrospective Study
ABSTRACT Introduction Neurological manifestations in children with hemoglobin SC (HbSC) disease remain insufficiently characterized, particularly regarding acute events. The aim of this study was to describe the spectrum and frequency of acute neurological events in a multicenter cohort of children with HbSC disease.
Célia Paulmin +11 more
wiley +1 more source
ABSTRACT Background Embryonal tumors comprise the majority of malignant central nervous system (CNS) neoplasms diagnosed in children under 3 years of age. Compared with their counterparts in older children, these tumors exhibit distinct molecular biology and a more aggressive clinical phenotype, while their management is complicated by the heightened ...
Sudarshawn Damodharan +3 more
wiley +1 more source
Missing values imputation using Fuzzy K-Top Matching Value
Missing data occurs when variables or observations are missing. Researchers exclude or impute influenced variables and data. This study proposes Fuzzy K-Top Matching Value (FKTM) for missing value imputation.
Azza Ali +3 more
doaj +1 more source
ABSTRACT Background Shwachman–Diamond syndrome (SDS) is a rare autosomal recessive ribosomopathy characterized by bone marrow failure and multisystem involvement, with emerging evidence of associated neurocognitive impairment. Methods We conducted a retrospective study of 240 individuals with biallelic Shwachman–Bodian–Diamond syndrome (SBDS) mutations
Jane Koo +11 more
wiley +1 more source

