AIMC Topic: Artificial Intelligence

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Exploring dental faculty awareness, knowledge, and attitudes toward AI integration in education and practice: a mixed-method study.

BMC medical education
BACKGROUND: Dentistry is shifting from traditional to digital practices owing to the rapid development of "artificial intelligence" (AI) technology in healthcare systems. The dental curriculum lacks the integration of emerging technologies such as AI...

AI usage among medical students in Palestine: a cross-sectional study and demonstration of AI-assisted research workflows.

BMC medical education
BACKGROUND: Artificial Intelligence (AI) is transforming medical education globally, offering solutions to challenges such as resource limitations and limited clinical exposure. However, its integration in resource-constrained settings like Palestine...

Interpretable artificial intelligence model for predicting heart failure severity after acute myocardial infarction.

BMC cardiovascular disorders
BACKGROUND: Heart failure (HF) after acute myocardial infarction (AMI) is a leading cause of mortality and morbidity worldwide. Accurate prediction and early identification of HF severity are crucial for initiating preventive measures and optimizing ...

Lead Informed Artificial Intelligence Mining of Antitubercular Host Defense Peptides.

Biomacromolecules
Identifying host defense peptides (HDPs) that are effective against drug-resistant infections is challenging due to their vast sequence space. Artificial intelligence (AI)-guided design can accelerate HDP discovery, but it traditionally requires larg...

EVOLVE: A Web Platform for AI-Based Protein Mutation Prediction and Evolutionary Phase Exploration.

Journal of chemical information and modeling
While predicting structure-function relationships from sequence data is fundamental in biophysical chemistry, identifying prospective single-point and collective mutation sites in proteins can help us stay ahead in understanding their potential effec...

AI-driven predictive biomarker discovery with contrastive learning to improve clinical trial outcomes.

Cancer cell
Modern clinical trials can capture tens of thousands of clinicogenomic measurements per individual. Discovering predictive biomarkers, as opposed to prognostic markers, remains challenging. To address this, we present a neural network framework based...

Molecular surfaces modeling: Advancements in deep learning for molecular interactions and predictions.

Biochemical and biophysical research communications
Molecular surface analysis can provide a high-dimensional, rich representation of molecular properties and interactions, which is crucial for enabling powerful predictive modeling and rational molecular design across diverse scientific and technologi...

Artificial intelligence voice gender, gender role congruity, and trust in automated vehicles.

Scientific reports
Existing research on human-automated vehicle (AV) interactions has largely focused on auditory explanations, with less attention to how voice characteristics shape user trust. This paper explores the influence of gender similarity between users and A...

[Surveillance for pneumonia of unknown etiology: current status, challenges, and implementation ways].

Zhonghua liu xing bing xue za zhi = Zhonghua liuxingbingxue zazhi
The prevention and control of emerging and reemerging infectious diseases are crucial for national biosecurity, and surveillance and reporting of pneumonia of unknown etiology are main ways for the early detection of these diseases and mitigation of ...

Using Masked Image Modelling Transformer Architecture for Laparoscopic Surgical Tool Classification and Localization.

Sensors (Basel, Switzerland)
Artificial intelligence (AI) has shown its potential to advance applications in various medical fields. One such area involves developing integrated AI-based systems to assist in laparoscopic surgery. Surgical tool detection and phase recognition are...