[HTML][HTML] Computational approaches to explainable artificial intelligence: advances in theory, applications and trends

JM Górriz, I Álvarez-Illán, A Álvarez-Marquina, JE Arco… - Information …, 2023 - Elsevier
Deep Learning (DL), a groundbreaking branch of Machine Learning (ML), has emerged as a
driving force in both theoretical and applied Artificial Intelligence (AI). DL algorithms, rooted …

Applications of artificial intelligence in the neuropsychological assessment of dementia: A systematic review

I Veneziani, A Marra, C Formica, A Grimaldi… - Journal of Personalized …, 2024 - mdpi.com
In the context of advancing healthcare, the diagnosis and treatment of cognitive disorders,
particularly Mild Cognitive Impairment (MCI) and Alzheimer's Disease (AD), pose significant …

An explainability artificial intelligence approach to brain connectivity in Alzheimer's disease

N Amoroso, S Quarto, M La Rocca… - Frontiers in Aging …, 2023 - frontiersin.org
The advent of eXplainable Artificial Intelligence (XAI) has revolutionized the way human
experts, especially from non-computational domains, approach artificial intelligence; this is …

[HTML][HTML] Identifying HRV patterns in ECG signals as early markers of dementia

JE Arco, NJ Gallego-Molina, A Ortiz… - Expert Systems with …, 2024 - Elsevier
Abstract The appearance of Artificial Intelligence (IA) has improved our ability to process
large amount of data. These tools are particularly interesting in medical contexts, in order to …

Multimodal Covariance Network Reflects Individual Cognitive Flexibility.

L Jiang, SB Eickhoff, S Genon, G Wang, C Yi… - International journal of …, 2024 - orbi.uliege.be
Cognitive flexibility refers to the capacity to shift between patterns of mental function and
relies on functional activity supported by anatomical structures. However, how the brain's …

Machine learning in small sample neuroimaging studies: Novel measures for schizophrenia analysis

C Jimenez‐Mesa, J Ramirez, Z Yi, C Yan… - Human Brain …, 2024 - Wiley Online Library
Novel features derived from imaging and artificial intelligence systems are commonly
coupled to construct computer‐aided diagnosis (CAD) systems that are intended as clinical …

Alzheimer's Disease Evaluation Through Visual Explainability by Means of Convolutional Neural Networks.

F Mercaldo, M Di Giammarco, F Ravelli… - … Journal of Neural …, 2024 - europepmc.org
Background and Objective: Alzheimer's disease is nowadays the most common cause of
dementia. It is a degenerative neurological pathology affecting the brain, progressively …

Validez discriminante y concordancia interobservador de 2 métodos de puntuación del test del reloj

T del Ser, B Frades, M Valentí-Soler… - Revista Española de …, 2023 - Elsevier
Objetivos Comparar la validez discriminante y la fiabilidad interobservador de los 2 métodos
de corrección del test del reloj más usados en España. Metodología Se han evaluado 2 …

Predicting Alzheimer's Disease and Mild Cognitive Impairment with Off-line and On-line House Drawing Tests

N Hosseini-Kivanani, E Salobrar-García… - 2024 IEEE 20th …, 2024 - ieeexplore.ieee.org
There is growing interest in developing reliable, non-invasive, and cost-effective methods for
early diagnosis of neurodegenerative diseases such as Mild Cognitive Impairment (MCI) …

Extracting Heart Rate Variability from NIRS Signals for an Explainable Detection of Learning Disorders

JE Arco, NJ Gallego-Molina, PJ López-Pérez… - … Work-Conference on …, 2024 - Springer
Artificial Intelligence (AI) has improved our ability to process large amounts of data. These
tools are particularly interesting in medical contexts because they evaluate the variables …