Cultural Competence

Algorithmic fairness in computational medicine.

Machine learning models are increasingly adopted for facilitating clinical decision-making. However,...

Natural Language Processing in Spine Surgery: A Systematic Review of Applications, Bias, and Reporting Transparency.

BACKGROUND: Natural language processing (NLP) is a discipline of machine learning concerned with the...

TAFM: A Recommendation Algorithm Based on Text-Attention Factorization Mechanism.

The click-through rate (CTR) prediction task is used to estimate the probabilities of users clicking...

Machine learning-assisted discovery of growth decision elements by relating bacterial population dynamics to environmental diversity.

Microorganisms growing in their habitat constitute a complex system. How the individual constituents...

Deep learning-based image deconstruction method with maintained saliency.

Visual properties that primarily attract bottom-up attention are collectively referred to as salienc...

When Does Diversity Help Generalization in Classification Ensembles?

Ensembles, as a widely used and effective technique in the machine learning community, succeed withi...

Data Augmentation for Deep-Learning-Based Multiclass Structural Damage Detection Using Limited Information.

The deterioration of infrastructure's health has become more predominant on a global scale during th...

What is the mission of innovation?-Lexical structure, sentiment analysis, and cosine similarity of mission statements of research-knowledge intensive institutions.

Mission statements (henceforth: missions) are strategic planning communication tools used by all typ...

De novo spatiotemporal modelling of cell-type signatures in the developmental human heart using graph convolutional neural networks.

With the emergence of high throughput single cell techniques, the understanding of the molecular and...

Machine-learning media bias.

We present an automated method for measuring media bias. Inferring which newspaper published a given...

Global Negative Correlation Learning: A Unified Framework for Global Optimization of Ensemble Models.

Ensembles are a widely implemented approach in the machine learning community and their success is t...

Explaining One-Dimensional Convolutional Models in Human Activity Recognition and Biometric Identification Tasks.

Due to wearables' popularity, human activity recognition (HAR) plays a significant role in people's ...

Prediction of Metabolic Characteristics of Cardiovascular and Cerebrovascular Diseases Based on Convolutional Neural Network.

As a typical disease, cardiovascular and cerebrovascular diseases cause great damage to the human bo...

Interpretability-Guided Inductive Bias For Deep Learning Based Medical Image.

Deep learning methods provide state of the art performance for supervised learning based medical ima...

Deep learning in periodontology and oral implantology: A scoping review.

Deep learning (DL) has been employed for a wide range of tasks in dentistry. We aimed to systematica...

Adaptive Dense Ensemble Model for Text Classification.

Text classification has been widely explored in natural language processing. In this article, we pro...

Validating Automatic Concept-Based Explanations for AI-Based Digital Histopathology.

Digital histopathology poses several challenges such as label noise, class imbalance, limited availa...

Diversity of approaches in artificial intelligence: an opportunity for discoveries in thoracic imaging.

KAT: A Knowledge Adversarial Training Method for Zero-Order Takagi-Sugeno-Kang Fuzzy Classifiers.

While input or output-perturbation-based adversarial training techniques have been exploited to enha...

Event-level prediction of urban crime reveals a signature of enforcement bias in US cities.

Policing efforts to thwart crime typically rely on criminal infraction reports, which implicitly man...

Exponential growth of systematic reviews assessing artificial intelligence studies in medicine: challenges and opportunities.

The evidence-based medicine (EBM) movement is stepping up its efforts to assess medical artificial i...