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TdCCA with Dual-Modal Signal Fusion: Degenerated Occipital and Frontal Connectivity of Adult Moyamoya Disease for Early Identification.

Translational stroke research
Cognitive impairment in patients with moyamoya disease (MMD) manifests earlier than clinical symptoms. Early identification of brain connectivity changes is essential for uncovering the pathogenesis of cognitive impairment in MMD. We proposed a tempo...

Synergic Integration of the miRNome, Machine Learning and Bioinformatics for the Identification of Potential Disease-Modifying Agents in Obstructive Sleep Apnea.

Archivos de bronconeumologia
INTRODUCTION: Understanding the diverse pathogenetic pathways in obstructive sleep apnea (OSA) is crucial for improving outcomes. microRNA (miRNA) profiling is a promising strategy for elucidating these mechanisms.

A pilot evaluation of school-based LEGO® robotics therapy for autistic students.

Disability and rehabilitation. Assistive technology
There is emerging evidence that LEGO® therapy is an effective way of supporting younger autistic children develop their communication and social skills. LEGO® robotics therapy - which uses the principles of LEGO® therapy applied to LEGO® robotics - m...

Early prediction of intensive care unit admission in emergency department patients using machine learning.

Australian critical care : official journal of the Confederation of Australian Critical Care Nurses
BACKGROUND: The timely identification and transfer of critically ill patients from the emergency department (ED) to the intensive care unit (ICU) is important for patient care and ED workflow practices.

A prognostic and predictive model based on deep learning to identify optimal candidates for intensity-modulated radiotherapy alone in patients with stage II nasopharyngeal carcinoma: A retrospective multicenter study.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
PURPOSE: To develop and validate a prognostic and predictive model integrating deep learning MRI features and clinical information in patients with stage II nasopharyngeal carcinoma (NPC) to identify patients with a low risk of progression for whom i...

Prediction based on machine learning of tooth sensitivity for in-office dental bleaching.

Journal of dentistry
OBJECTIVE: To develop a supervised machine learning model to predict the occurrence and intensity of tooth sensitivity (TS) in patients undergoing in-office dental bleaching testing various algorithm models.

When the bot walks the talk: Investigating the foundations of trust in an artificial intelligence (AI) chatbot.

Journal of experimental psychology. General
The concept of trust in artificial intelligence (AI) has been gaining increasing relevance for understanding and shaping human interaction with AI systems. Despite a growing literature, there are disputes as to whether the processes of trust in AI ar...

View-symmetric representations of faces in human and artificial neural networks.

Neuropsychologia
View symmetry has been suggested to be an important intermediate representation between view-specific and view-invariant representations of faces in the human brain. Here, we compared view-symmetry in humans and a deep convolutional neural network (D...

Development and validation of a machine-learning model to predict lymph node metastasis of intrahepatic cholangiocarcinoma: A retrospective cohort study.

Bioscience trends
Lymph node metastasis in intrahepatic cholangiocarcinoma significantly impacts overall survival, emphasizing the need for a predictive model. This study involved patients who underwent curative liver resection between different time periods. Three ma...

Evaluating CNN Architectures for the Automated Detection and Grading of Modic Changes in MRI: A Comparative Study.

Orthopaedic surgery
OBJECTIVE: Modic changes (MCs) classification system is the most widely used method in magnetic resonance imaging (MRI) for characterizing subchondral vertebral marrow changes. However, it shows a high degree of sensitivity to variations in MRI becau...