Cultural Competence

Utilizing InVEST ecosystem services model combined with deep learning and fallback bargaining for effective sediment retention in Northern Iran.

This study aimed to integrate game theory and deep learning algorithms with the InVEST Ecosystem Services Model (IESM) for Sediment Retention (SR) modeling in the Kasilian watershed, Iran. The Kasilian watershed is characterized by multiple sub-watersheds, which vary in their environmental conditions and SR potential, with a total of 19 sub-watersheds. The research was carried out in four phases: ...

Exploiting passive behaviours for diverse musical playing using the parametric hand.

Creativity and style in music playing originates from constraints and imperfect interactions between instruments and players. Digital and robotic systems have so far been unable to capture this naturalistic playing. Whether as an additional tool for musicians, function restoration with prosthetics, or artificial intelligence-powered systems, the physical embodiment and interactions generated are c...

Where, why, and how is bias learned in medical image analysis models? A study of bias encoding within convolutional networks using synthetic data.

BACKGROUND: Understanding the mechanisms of algorithmic bias is highly challenging due to the complexity and uncertainty of how various unknown source...

Accelerating the pace of innovation in robotics by fostering diversity and inclusive leadership.

Diverse and inclusive teams are not merely a moral imperative but also a catalyst for scientific excellence in robotics. Drawing from literature, a co...

AI in Biomedicine-A Forward-Looking Perspective on Health Equity.

As new artificial intelligence (AI) tools are being developed and as AI continues to revolutionize healthcare, its potential to advance health equity ...

Automated segmentation of dental restorations using deep learning: exploring data augmentation techniques.

OBJECTIVES: Deep learning has revolutionized image analysis for dentistry. Automated segmentation of dental radiographs is of great importance towards...

A multi-memory-augmented network with a curvy metric method for video anomaly detection.

Anomaly detection task in video mainly refers to identifying anomalous events that do not conform to the learned normal patterns in the inferring phas...

Domain generalization for mammographic image analysis with contrastive learning.

The deep learning technique has been shown to be effectively addressed several image analysis tasks in the computer-aided diagnosis scheme for mammogr...

Integrating microbial profiling and machine learning for inference of drowning sites: a forensic investigation in the Northwest River.

Drowning incidents present significant challenges for forensic investigators in determining the exact site of occurrence. Traditional forensic methods...

Semantic Mask Reconstruction and Category Semantic Learning for few-shot image generation.

Few-shot image generation aims at generating novel images for the unseen category when given K images from the same category. Despite significant adva...

Spatiotemporal Deep Learning-Based Cine Loop Quality Filter for Handheld Point-of-Care Echocardiography.

The reliability of automated image interpretation of point-of-care (POC) echocardiography scans depends on the quality of the acquired ultrasound data...

Arithmetic abilities of SNP systems with astrocytes producing calcium.

Are the membrane systems able of performing arithmetic operations? In the last dozen years, there were published several implementations of the arithm...

The role of artificial intelligence in enhancing healthcare for people with disabilities.

The integration of artificial intelligence (AI) in healthcare delivery represents a transformative opportunity to enhance the lives of people living w...

Integrating large language models in systematic reviews: a framework and case study using ROBINS-I for risk of bias assessment.

Large language models (LLMs) may facilitate and expedite systematic reviews, although the approach to integrate LLMs in the review process is unclear....

Evaluating predictive artificial intelligence approaches used in mobile health platforms to forecast mental health symptoms among youth: a systematic review.

The youth mental health crisis is exacerbated by limited access to care and resources. Mobile health (mHealth) platforms using predictive artificial i...

Comparative Analysis of Machine-Learning Model Performance in Image Analysis: The Impact of Dataset Diversity and Size.

BACKGROUND: This study presents an analysis of machine-learning model performance in image analysis, with a specific focus on videolaryngoscopy proced...

EDAI Framework for Integrating Equity, Diversity, and Inclusion Throughout the Lifecycle of AI to Improve Health and Oral Health Care: Qualitative Study.

BACKGROUND: Recent studies have identified significant gaps in equity, diversity, and inclusion (EDI) considerations within the lifecycle of artificia...

Entrustment and EPAs for Artificial Intelligence (AI): A Framework to Safeguard the Use of AI in Health Professions Education.

In this article, the authors propose a repurposing of the concept of entrustment to help guide the use of artificial intelligence (AI) in health profe...

Sociodemographic bias in clinical machine learning models: a scoping review of algorithmic bias instances and mechanisms.

BACKGROUND AND OBJECTIVES: Clinical machine learning (ML) technologies can sometimes be biased and their use could exacerbate health disparities. The ...

Artificial Intelligence Efficacy as a Function of Trainee Interpreter Proficiency: Lessons from a Randomized Controlled Trial.

BACKGROUND AND PURPOSE: Recently, artificial intelligence tools have been deployed with increasing speed in educational and clinical settings. However...