AIMC Topic: Cognition
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A machine learning approach for differentiating bipolar disorder type II and borderline personality disorder using electroencephalography and cognitive abnormalities.
PloS one
Jun 21, 2024
This study addresses the challenge of differentiating between bipolar disorder II (BD II) and borderline personality disorder (BPD), which is complicated by overlapping symptoms. To overcome this, a multimodal machine learning approach was employed, ...
Cluster-CAM: Cluster-weighted visual interpretation of CNNs' decision in image classification.
Neural networks : the official journal of the International Neural Network Society
Jun 20, 2024
Despite the tremendous success of convolutional neural networks (CNNs) in computer vision, the mechanism of CNNs still lacks clear interpretation. Currently, class activation mapping (CAM), a famous visualization technique to interpret CNN's decision...
Dynamically predicting comprehension difficulties through physiological data and intelligent wearables.
Scientific reports
Jun 13, 2024
Comprehending digital content written in natural language online is vital for many aspects of life, including learning, professional tasks, and decision-making. However, facing comprehension difficulties can have negative consequences for learning ou...
Driving Cognitive Alertness Detecting Using Evoked Multimodal Physiological Signals Based on Uncertain Self-Supervised Learning.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Jun 13, 2024
Multimodal physiological signals play a pivotal role in drivers' perception of work stress. However, the scarcity of labels and the multitude of modalities render the utilization of physiological signals for driving cognitive alertness detection chal...
Machine learning approach to classifying declines of physical function and muscle strength associated with cognitive function in older women: gait characteristics based on three speeds.
Frontiers in public health
Jun 12, 2024
BACKGROUND: The aging process is associated with a cognitive and physical declines that affects neuromotor control, memory, executive functions, and motor abilities. Previous studies have made efforts to find biomarkers, utilizing complex factors suc...
Assessing the anticholinergic cognitive burden classification of putative anticholinergic drugs using drug properties.
British journal of clinical pharmacology
Jun 11, 2024
AIMS: This study evaluated the use of machine learning to leverage drug absorption, distribution, metabolism and excretion (ADME) data together with physicochemical and pharmacological data to develop a novel anticholinergic burden scale and compare ...
Development of a Personalized Multiclass Classification Model to Detect Blood Pressure Variations Associated with Physical or Cognitive Workload.
Sensors (Basel, Switzerland)
Jun 6, 2024
Comprehending the regulatory mechanisms influencing blood pressure control is pivotal for continuous monitoring of this parameter. Implementing a personalized machine learning model, utilizing data-driven features, presents an opportunity to facilita...
Synergistic information supports modality integration and flexible learning in neural networks solving multiple tasks.
PLoS computational biology
Jun 3, 2024
Striking progress has been made in understanding cognition by analyzing how the brain is engaged in different modes of information processing. For instance, so-called synergistic information (information encoded by a set of neurons but not by any sub...
Automated discovery of symbolic laws governing skill acquisition from naturally occurring data.
Nature computational science
May 24, 2024
Skill acquisition is a key area of research in cognitive psychology as it encompasses multiple psychological processes. The laws discovered under experimental paradigms are controversial and lack generalizability. This paper aims to unearth the laws ...
Understanding Human Cognition Through Computational Modeling.
Topics in cognitive science
May 23, 2024
One important goal of cognitive science is to understand the mind in terms of its representational and computational capacities, where computational modeling plays an essential role in providing theoretical explanations and predictions of human behav...
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