AIMC Topic: Young Adult
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AcidAGE: a biological age determination neural network based on urine organic acids.
Biogerontology
Dec 6, 2024
Organic acids reflect the course of all important metabolic processes and the effects of diet, nutrient deficiency, lifestyle, and microbiota composition. In present work, we focused on identifying age-related changes in organic acids in urine, and c...
TdCCA with Dual-Modal Signal Fusion: Degenerated Occipital and Frontal Connectivity of Adult Moyamoya Disease for Early Identification.
Translational stroke research
Dec 5, 2024
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...
Prediction based on machine learning of tooth sensitivity for in-office dental bleaching.
Journal of dentistry
Dec 5, 2024
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
Dec 5, 2024
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
Dec 5, 2024
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...
Machine learning-based prediction of antibiotic resistance in Mycobacterium tuberculosis clinical isolates from Uganda.
BMC infectious diseases
Dec 5, 2024
BACKGROUND: Efforts toward tuberculosis management and control are challenged by the emergence of Mycobacterium tuberculosis (MTB) resistance to existing anti-TB drugs. This study aimed to explore the potential of machine learning algorithms in predi...
Young Adult
Adult
Male
Middle Aged
Polymorphism, Single Nucleotide
Antitubercular Agents
South Africa
Microbial Sensitivity Tests
Uganda
Humans
Machine Learning
Drug Resistance, Bacterial
Female
Rifampin
Tuberculosis, Multidrug-Resistant
Streptomycin
Whole Genome Sequencing
Mycobacterium tuberculosis
Isoniazid
Detection of three-rooted mandibular first molars on panoramic radiographs using deep learning.
Scientific reports
Dec 5, 2024
This study aimed to develop a deep learning system for the detection of three-rooted mandibular first molars (MFMs) on panoramic radiographs and to assess its diagnostic performance. Panoramic radiographs, together with cone beam computed tomographic...
Generative models of MRI-derived neuroimaging features and associated dataset of 18,000 samples.
Scientific data
Dec 5, 2024
Availability of large and diverse medical datasets is often challenged by privacy and data sharing restrictions. Successful application of machine learning techniques for disease diagnosis, prognosis, and precision medicine, requires large amounts of...
Machine Learning-Based Suicide Risk Prediction Model for Suicidal Trajectory on Social Media Following Suicidal Mentions: Independent Algorithm Validation.
Journal of medical Internet research
Dec 5, 2024
BACKGROUND: Previous efforts to apply machine learning-based natural language processing to longitudinally collected social media data have shown promise in predicting suicide risk.
Sleep Stage Classification Via Multi-View Based Self-Supervised Contrastive Learning of EEG.
IEEE journal of biomedical and health informatics
Dec 5, 2024
Self-supervised learning (SSL) is a challenging task in sleep stage classification (SSC) that is capable of mining valuable representations from unlabeled data. However, traditional SSL methods typically focus on single-view learning and do not fully...
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