Interference effects from machine learning matched confusable object pairs in memory assessment tasks

Interference effects from machine learning matched confusable object pairs in memory assessment tasks

<p>For early detection of neurodegeneration, objective cognitive tests provide a capable alternative to costly and invasive traditional biomarkers, as well as to short and infrequent in-clinic cognitive assessments. These tests, that are designed to target the cognitive processes first vulnera...

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Bibliografiske detaljer
Hovedforfatter:	Batra, D
Andre forfattere:	Hinds, C
Format:	Thesis
Sprog:	English
Udgivet:	2022
Fag:	Statistics Psychiatry Deep learning (Machine learning) Multilevel models (Statistics) Computational neuroscience

Lignende værker

Machine learning and statistical models to address cluster-level confounding for the study of medical devices and surgical epidemiology using observational data
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Advantages of Machine Learning in Forensic Psychiatric Research—Uncovering the Complexities of Aggressive Behavior in Schizophrenia
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Probabilistic models and Monte Carlo objectives in generative modelling
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Towards data-efficient deep learning with meta-learning and symmetries
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Automated data acquisition via Bayesian experimental design
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Towards trustworthy machine learning with kernels
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The evolutionary origin of Bayesian heuristics and finite memory
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Robustness, structure and hierarchy in deep generative models
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Comprehensive review of Transformer‐based models in neuroscience, neurology, and psychiatry
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Objective assessment of Parkinson's disease using machine learning
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Udgivet: (2018)

Enabling feature-level interpretability in non-linear latent variable models: a synthesis of statistical and machine learning techniques
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Udgivet: (2019)

Neural networks for inference, inference for neural networks
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Udgivet: (2018)

Empirical performance of simple statistical inference-type models with feature extraction in comparison to modern machine learning methods concerning regression and classification problems
af: Dittgen, M
Udgivet: (2019)

Inference and applications of genetic relatedness in human populations
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Udgivet: (2022)

Enhancing fraud detection in auto insurance and credit card transactions: a novel approach integrating CNNs and machine learning algorithms
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Mixed effects models for complex data /
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Paired Trial Classification: A Novel Deep Learning Technique for MVPA
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Udgivet: (2020-04-01)

A software system for analyzing the statistics of football matches and predicting the results based on machine learning
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Udgivet: (2022-12-01)

Logical factorisation machines: probabilistic boolean factor models for binary data
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Udgivet: (2018)

Rapid encoding of task regularities in the human hippocampus guides sensorimotor timing
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Udgivet: (2022-11-01)

The SAGE handbook of multilevel modeling /
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Udgivet: (2013)

The impact of centering first-level predictors on individual and contextual effects in multilevel data analysis/
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Application of multilevel modeling in educational data /
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Udgivet: (2014)

Fast identification and quantification of c-Fos protein using you-only-look-once-v5
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Udgivet: (2022-09-01)

Statistical Methods with Applications in Data Mining: A Review of the Most Recent Works
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Udgivet: (2022-03-01)

Variational, Monte Carlo and policy-based approaches to Bayesian experimental design
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Udgivet: (2021)

Autobiographical memories, identity disturbance and brain functioning in patients with borderline personality disorder: An fMRI study
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Udgivet: (2019-03-01)

Editorial: Machine and deep-learning for computational neuroscience
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Suicidal Offenders and Non-Offenders with Schizophrenia Spectrum Disorders: A Retrospective Evaluation of Distinguishing Factors Using Machine Learning
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Mediators of transdiagnostic psychological treatments for eating disorders
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Udgivet: (2017)

A Survey of Uncertainty Quantification in Machine Learning for Space Weather Prediction
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Udgivet: (2022-01-01)

Large scale methods for kernels, causal inference and survival modelling
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Udgivet: (2022)

Generative models: theory and applications
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Udgivet: (2023)

On the properties of random feature methods
af: Li, Z
Udgivet: (2020)

Testing and learning on distributional and set inputs
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Udgivet: (2019)

Sample Size Analysis for Machine Learning Clinical Validation Studies
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Machine Learning for Neuroimaging with Scikit-Learn
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Inference on Markov random fields: methods and applications
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Udgivet: (2017)

Unimodal statistical learning produces multimodal object-like representations
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Udgivet: (2019-05-01)