Cultural Competence

Transformer-CNN hybrid network for improving PET time of flight prediction.

In positron emission tomography (PET) reconstruction, the integration of time-of-flight (TOF) inform...

Evaluating initial usability of a hand augmentation device across a large and diverse sample.

The advancement of motor augmentation and the broader domain of human-machine interaction rely on a ...

Structure-aware machine learning strategies for antimicrobial peptide discovery.

Machine learning models are revolutionizing our approaches to discovering and designing bioactive pe...

Evaluating the Diversity and Representation of Artificial Intelligence-Generated Images of Radiologists: An Observational Study.

Enhancing aspect-based multi-labeling with ensemble learning for ethical logistics.

In the dynamic domain of logistics, effective communication is essential for streamlined operations....

A machine learning approach to classifying New York Heart Association (NYHA) heart failure.

According to the European Society of Cardiology, globally the number of patients with heart failure ...

Parkinson's Disease Recognition Using Decorrelated Convolutional Neural Networks: Addressing Imbalance and Scanner Bias in rs-fMRI Data.

Parkinson's disease (PD) is a neurodegenerative and progressive disease that impacts the nerve cells...

Adaptively identify and refine ill-posed regions for accurate stereo matching.

Stereo matching cost constrains the consistency between pixel pairs. However, the consistency constr...

Implications of Large Language Models for Quality and Efficiency of Neurologic Care: Emerging Issues in Neurology.

Large language models (LLMs) are advanced artificial intelligence (AI) systems that excel in recogni...

Advancing Fairness in Cardiac Care: Strategies for Mitigating Bias in Artificial Intelligence Models Within Cardiology.

In the dynamic field of medical artificial intelligence (AI), cardiology stands out as a key area fo...

Prospective evaluation of artificial intelligence (AI) applications for use in cancer pathways following diagnosis: a systematic review.

The role of artificial intelligence (AI) in cancer care has evolved in the face of ageing population...

Gender Bias in Artificial Intelligence-Written Letters of Reference.

OBJECTIVE: Letters of reference (LORs) play an important role in postgraduate residency applications...

Bias-reduced neural networks for parameter estimation in quantitative MRI.

PURPOSE: To develop neural network (NN)-based quantitative MRI parameter estimators with minimal bia...

Exploring the Association Between Structural Racism and Mental Health: Geospatial and Machine Learning Analysis.

BACKGROUND: Structural racism produces mental health disparities. While studies have examined the im...

Deep learning in magnetic resonance enterography for Crohn's disease assessment: a systematic review.

Crohn's disease (CD) poses significant morbidity, underscoring the need for effective, non-invasive ...

A survey of recent methods for addressing AI fairness and bias in biomedicine.

OBJECTIVES: Artificial intelligence (AI) systems have the potential to revolutionize clinical practi...

Large Language Models and User Trust: Consequence of Self-Referential Learning Loop and the Deskilling of Health Care Professionals.

As the health care industry increasingly embraces large language models (LLMs), understanding the co...

Enhanced Spatial Fuzzy C-Means Algorithm for Brain Tissue Segmentation in T1 Images.

Magnetic Resonance Imaging (MRI) plays an important role in neurology, particularly in the precise s...

Use of natural language processing to uncover racial bias in obstetrical documentation.

Natural Language Processing (NLP), a form of Artificial Intelligence, allows free-text based clinica...

DeepReg: a deep learning hybrid model for predicting transcription factors in eukaryotic and prokaryotic genomes.

Deep learning models (DLMs) have gained importance in predicting, detecting, translating, and classi...

Characterising global antimicrobial resistance research explains why One Health solutions are slow in development: An application of AI-based gap analysis.

The global health crisis posed by increasing antimicrobial resistance (AMR) implicitly requires solu...