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Evaluating the performance of the cognitive workload model with subjective endorsement in addition to EEG.
Medical & biological engineering & computing
Mar 3, 2024
The aptitude-oriented exercises from almost all domains impose cognitive load on their operators. Evaluating such load poses several challenges owing to many factors like measurement mode and complexity, nature of the load, overloading conditions, et...
A Prospective Study of Machine Learning-Assisted Radiation Therapy Planning for Patients Receiving 54 Gy to the Brain.
International journal of radiation oncology, biology, physics
Mar 1, 2024
PURPOSE: The capacity for machine learning (ML) to facilitate radiation therapy (RT) planning for primary brain tumors has not been described. We evaluated ML-assisted RT planning with regard to clinical acceptability, dosimetric outcomes, and planni...
Deep Learning Radiomics Analysis of CT Imaging for Differentiating Between Crohn's Disease and Intestinal Tuberculosis.
Journal of imaging informatics in medicine
Feb 29, 2024
This study aimed to develop and evaluate a CT-based deep learning radiomics model for differentiating between Crohn's disease (CD) and intestinal tuberculosis (ITB). A total of 330 patients with pathologically confirmed as CD or ITB from the First Af...
Enhancing neural encoding models for naturalistic perception with a multi-level integration of deep neural networks and cortical networks.
Science bulletin
Feb 29, 2024
Cognitive neuroscience aims to develop computational models that can accurately predict and explain neural responses to sensory inputs in the cortex. Recent studies attempt to leverage the representation power of deep neural networks (DNNs) to predic...
Deep learning segmentation of the choroid plexus from structural magnetic resonance imaging (MRI): validation and normative ranges across the adult lifespan.
Fluids and barriers of the CNS
Feb 29, 2024
BACKGROUND: The choroid plexus functions as the blood-cerebrospinal fluid (CSF) barrier, plays an important role in CSF production and circulation, and has gained increased attention in light of the recent elucidation of CSF circulation dysfunction i...
Decoding emotions: Exploring the validity of sentiment analysis in psychotherapy.
Psychotherapy research : journal of the Society for Psychotherapy Research
Feb 28, 2024
OBJECTIVE: Given the importance of emotions in psychotherapy, valid measures are essential for research and practice. As emotions are expressed at different levels, multimodal measurements are needed for a nuanced assessment. Natural Language Process...
Estimating Body Weight From Measurements From Different Single-Slice Computed Tomography Levels: An Evaluation of Total Cross-Sectional Body Area Measurements and Deep Learning.
Journal of computer assisted tomography
Feb 27, 2024
OBJECTIVE: This study aimed to evaluate the correlation between the estimated body weight obtained from 2 easy-to-perform methods and the actual body weight at different computed tomography (CT) levels and determine the best reference site for estima...
Residual facial erythema in atopic dermatitis patients treated with dupilumab stratified by machine learning.
Journal of the European Academy of Dermatology and Venereology : JEADV
Feb 26, 2024
BACKGROUND: Persistent facial erythema represents a significant complication in atopic dermatitis (AD) patients undergoing treatment with dupilumab. Stratifying patients based on the erythema course is crucial for elucidating heterogeneous phenotypes...
Radiography students' perceptions of artificial intelligence in medical imaging.
Journal of medical imaging and radiation sciences
Feb 24, 2024
INTRODUCTION: Education relating to Artificial Intelligence (AI) is becoming critical to developing contemporary radiographers. This study sought to investigate the perceptions of a sample of Australian radiography students regarding AI within the co...
Predicting Soccer Players' Fitness Status Through a Machine-Learning Approach.
International journal of sports physiology and performance
Feb 24, 2024
PURPOSE: The study had 3 purposes: (1) to develop an index using machine-learning techniques to predict the fitness status of soccer players, (2) to explore the index's validity and its relationship with a submaximal run test (SMFT), and (3) to analy...
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