Cultural Competence

SGPPI: structure-aware prediction of protein-protein interactions in rigorous conditions with graph convolutional network.

While deep learning (DL)-based models have emerged as powerful approaches to predict protein-protein...

Evaluation of diagnosis diversity in artificial intelligence datasets: a scoping review.

Growing ecosystem of deep learning methods for modeling protein-protein interactions.

Numerous cellular functions rely on protein-protein interactions. Efforts to comprehensively charact...

The Bias-Variance Tradeoff in Cognitive Science.

The bias-variance tradeoff is a theoretical concept that suggests machine learning algorithms are su...

Recommendations for the development and use of imaging test sets to investigate the test performance of artificial intelligence in health screening.

Rigorous evaluation of artificial intelligence (AI) systems for image classification is essential be...

Detrimental Detection of Advanced Lesions With AI: False Confidence or Prevalence Bias?

Picture a data scientist: a call to action for increasing diversity, equity, and inclusion in the age of AI.

The lack of diversity, equity, and inclusion continues to hamper the artificial intelligence (AI) fi...

Key role of neuronal diversity in structured reservoir computing.

Chaotic time series have been captured by reservoir computing models composed of a recurrent neural ...

Tackling bias in AI health datasets through the STANDING Together initiative.

MAMnet: detecting and genotyping deletions and insertions based on long reads and a deep learning approach.

Structural variations (SVs) play important roles in human genetic diversity; deletions and insertion...

Statistical neural network (SNN) for predicting signal-to-noise ratio (SNR) from static parameters and its validation in 16-bit, 125-MSPS analog-to-digital converters (ADCs).

In the analog-to-digital converter (ADC) test process, the static and dynamic performance parameters...

Addressing the Intra-class Mode Collapse Problem using Adaptive Input Image Normalization in GAN-based X-ray Images.

Biomedical image datasets can be imbalanced due to the rarity of targeted diseases. Generative Adver...

Performance Evaluation of Embedded Image Classification Models Using Edge Impulse for Application on Medical Images.

This work explores the possibility of applying edge machine learning technology in the context of po...

Assessing socioeconomic bias in machine learning algorithms in health care: a case study of the HOUSES index.

OBJECTIVE: Artificial intelligence (AI) models may propagate harmful biases in performance and hence...

Artificial Intelligence and Machine Learning Technologies in Cancer Care: Addressing Disparities, Bias, and Data Diversity.

Artificial intelligence (AI) and machine learning (ML) technologies have not only tremendous potenti...

Artificial Intelligence and Medical Humanities.

The use of artificial intelligence in healthcare has led to debates about the role of human clinicia...

Preprocessing to Address Bias in Healthcare Data.

Multimorbidity, having a diagnosis of two or more chronic conditions, increases as people age. It is...

Regulating the Safety of Health-Related Artificial Intelligence.

This article analyzes whether Canada's present approach to regulating health-related artificial inte...

Artificial Intelligence in Oncology: Current Capabilities, Future Opportunities, and Ethical Considerations.

The promise of highly personalized oncology care using artificial intelligence (AI) technologies has...

Artificial intelligence for older people receiving long-term care: a systematic review of acceptability and effectiveness studies.

Artificial intelligence (AI)-enhanced interventions show promise for improving the delivery of long-...

Investigating for bias in healthcare algorithms: a sex-stratified analysis of supervised machine learning models in liver disease prediction.

OBJECTIVES: The Indian Liver Patient Dataset (ILPD) is used extensively to create algorithms that pr...