AIMC Topic: Artificial Intelligence

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The Genie Is Out of the Bottle: What ChatGPT Can and Cannot Do for Medical Professionals.

Obstetrics and gynecology
ChatGPT is a cutting-edge artificial intelligence technology that was released for public use in November 2022. Its rapid adoption has raised questions about capabilities, limitations, and risks. This article presents an overview of ChatGPT, and it h...

Deep learning(s) in gaming disorder through the user-avatar bond: A longitudinal study using machine learning.

Journal of behavioral addictions
BACKGROUND AND AIMS: Gaming disorder [GD] risk has been associated with the way gamers bond with their visual representation (i.e., avatar) in the game-world. More specifically, a gamer's relationship with their avatar has been shown to provide relia...

Structural insights into gating mechanism and allosteric regulation of NMDA receptors.

Current opinion in neurobiology
N-methyl-d-aspartate receptors (NMDARs) belong to the ionotropic glutamate receptors (iGluRs) superfamily and act as coincidence detectors that are crucial to neuronal development and synaptic plasticity. They typically assemble as heterotetramers of...

Anatomy of Potency Predictions Focusing on Structural Analogues with Increasing Potency Differences Including Activity Cliffs.

Journal of chemical information and modeling
Potency predictions are popular in compound design and optimization but are complicated by intrinsic limitations. Moreover, even for nonlinear methods, activity cliffs (ACs, formed by structural analogues with large potency differences) represent cha...

Toward a Vision-Based Intelligent System: A Stacked Encoded Deep Learning Framework for Sign Language Recognition.

Sensors (Basel, Switzerland)
Sign language recognition, an essential interface between the hearing and deaf-mute communities, faces challenges with high false positive rates and computational costs, even with the use of advanced deep learning techniques. Our proposed solution is...

A Novel Machine-Learning Framework Based on a Hierarchy of Dispute Models for the Identification of Fish Species Using Multi-Mode Spectroscopy.

Sensors (Basel, Switzerland)
Seafood mislabeling rates of approximately 20% have been reported globally. Traditional methods for fish species identification, such as DNA analysis and polymerase chain reaction (PCR), are expensive and time-consuming, and require skilled technicia...

Orthodontic Implementation of Machine Learning Algorithms for Predicting Some Linear Dental Arch Measurements and Preventing Anterior Segment Malocclusion: A Prospective Study.

Medicina (Kaunas, Lithuania)
: Orthodontics is a field that has seen significant advancements in recent years, with technology playing a crucial role in improving diagnosis and treatment planning. The study aimed to implement artificial intelligence to predict the arch width as ...

The Impact of Data on Structure-Based Binding Affinity Predictions Using Deep Neural Networks.

International journal of molecular sciences
Artificial intelligence (AI) has gained significant traction in the field of drug discovery, with deep learning (DL) algorithms playing a crucial role in predicting protein-ligand binding affinities. Despite advancements in neural network architectur...

Efficient automated error detection in medical data using deep-learning and label-clustering.

Scientific reports
Medical datasets inherently contain errors from subjective or inaccurate test results, or from confounding biological complexities. It is difficult for medical experts to detect these elusive errors manually, due to lack of contextual information, li...