Clinical use and implementation of the diagnostic classification of mental health and developmental disorders of infancy and early childhood.
Sign Up to like & getrecommendations! Published in 2023 at "Infant mental health journal"
DOI: 10.1002/imhj.22054
Abstract: The Diagnostic Classification of Mental Health and Developmental Disorders of Infancy and Early Childhood (DC: 0-5) was developed to provide a framework for diagnosis of infants and young children, and a training curriculum supports implementation… read more here.
Keywords: health; mental health; classification mental; implementation ... See more keywords
A Generalized Diagnostic Classification Modeling Framework Integrating Differential Speediness: Advantages and Illustrations in Psychological and Educational Testing.
Sign Up to like & getrecommendations! Published in 2021 at "Multivariate behavioral research"
DOI: 10.1080/00273171.2021.1928474
Abstract: To advance the theoretical foundation of incorporating response times (RTs) into diagnostic classification models (DCMs), this study attempts to further derive, test and illustrate a generalized modeling framework (known as the JVRT-LCDM) that can simultaneously… read more here.
Keywords: modeling framework; diagnostic classification; jvrt lcdm; lcdm ... See more keywords
S152. DIAGNOSTIC CLASSIFICATION OF SCHIZOPHRENIA USING 3D CONVOLUTIONAL NEURAL NETWORK WITH RESTING-STATE FUNCTIONAL MRI
Sign Up to like & getrecommendations! Published in 2020 at "Schizophrenia Bulletin"
DOI: 10.1093/schbul/sbaa031.218
Abstract: Abstract Background Several machine-learning (ML) algorithms have been deployed in the diagnostic classification of schizophrenia. Compared to other ML methods, the 3D convolutional neural network (CNN) has an advantage of learning complex and subtle patterns… read more here.
Keywords: schizophrenia; classification; classification schizophrenia; resting state ... See more keywords
Functional Connectivity-Based Prediction of Autism on Site Harmonized ABIDE Dataset
Sign Up to like & getrecommendations! Published in 2021 at "IEEE Transactions on Biomedical Engineering"
DOI: 10.1109/tbme.2021.3080259
Abstract: Objective: The larger sample sizes available from multi-site publicly available neuroimaging data repositories makes machine-learning based diagnostic classification of mental disorders more feasible by alleviating the curse of dimensionality. However, since multi-site data are aggregated… read more here.
Keywords: diagnostic classification; site; autism; connectivity ... See more keywords
M₂DC: A Meta-Learning Framework for Generalizable Diagnostic Classification of Major Depressive Disorder
Sign Up to like & getrecommendations! Published in 2024 at "IEEE Transactions on Medical Imaging"
DOI: 10.1109/tmi.2024.3461312
Abstract: Psychiatric diseases are bringing heavy burdens for both individual health and social stability. The accurate and timely diagnosis of the diseases is essential for effective treatment and intervention. Thanks to the rapid development of brain… read more here.
Keywords: classification; brain; major depressive; classification major ... See more keywords
Evaluation of the NANDA International, Inc. diagnostic classification in Spain: Development and validation of the EVALUAN‐I tool
Sign Up to like & getrecommendations! Published in 2022 at "International Journal of Nursing Knowledge"
DOI: 10.1111/2047-3095.12366
Abstract: Abstract Purpose To develop and validate a tool to evaluate the NANDA International, Inc. diagnostic classification. Methods The tool, EVALUAN‐I, was validated in a non‐probabilistic sample (N = 460) on Spanish Registered Nurses (September–December 2019)… read more here.
Keywords: inc diagnostic; classification; nanda international; international inc ... See more keywords
Impact of mismatches in HbA1c vs glucose values on the diagnostic classification of diabetes and prediabetes
Sign Up to like & getrecommendations! Published in 2019 at "Diabetic Medicine"
DOI: 10.1111/dme.14181
Abstract: To determine whether HbA1c mismatches (HbA1c levels that are higher or lower than expected for the average glucose levels in different individuals) could lead to errors if diagnostic classification is based only on HbA1c levels. read more here.
Keywords: impact mismatches; glucose values; mismatches hba1c; hba1c glucose ... See more keywords
Correct diagnostic classification and treatment of pneumonia symptoms in under-five children, northwest Ethiopia: a cross-sectional study
Sign Up to like & getrecommendations! Published in 2025 at "BMJ Paediatrics Open"
DOI: 10.1136/bmjpo-2025-003311
Abstract: Introduction Despite Ethiopia’s adoption of the Integrated Management of Newborn and Childhood Illnesses (IMNCI) strategy, pneumonia continues to be the leading infectious cause of death among under-five children. Therefore, this study aimed to determine the… read more here.
Keywords: classification; treatment; pneumonia symptoms; classification treatment ... See more keywords
Diagnostic Classification Model for Forced-Choice Items and Noncognitive Tests
Sign Up to like & getrecommendations! Published in 2022 at "Educational and Psychological Measurement"
DOI: 10.1177/00131644211069906
Abstract: The forced-choice (FC) item formats used for noncognitive tests typically develop a set of response options that measure different traits and instruct respondents to make judgments among these options in terms of their preference to… read more here.
Keywords: diagnostic classification; classification; noncognitive tests; model ... See more keywords
Improved Wald Statistics for Item-Level Model Comparison in Diagnostic Classification Models
Sign Up to like & getrecommendations! Published in 2019 at "Applied Psychological Measurement"
DOI: 10.1177/0146621618798664
Abstract: Diagnostic classification models (DCMs) have been widely used in education, psychology, and many other disciplines. To select the most appropriate DCM for each item, the Wald test has been recommended. However, prior research has revealed… read more here.
Keywords: test; level model; classification models; diagnostic classification ... See more keywords
Applying Negative Binomial Distribution in Diagnostic Classification Models for Analyzing Count Data
Sign Up to like & getrecommendations! Published in 2022 at "Applied Psychological Measurement"
DOI: 10.1177/01466216221124604
Abstract: Diagnostic classification models (DCMs) have been used to classify examinees into groups based on their possession status of a set of latent traits. In addition to traditional item-based scoring approaches, examinees may be scored based… read more here.
Keywords: classification models; binomial distribution; negative binomial; count ... See more keywords