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Cultural Competence

Latest AI and machine learning research in cultural competence for healthcare professionals.

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Afann: bias adjustment for alignment-free sequence comparison based on sequencing data using neural network regression.

Alignment-free methods, more time and memory efficient than alignment-based methods, have been widel...

Development of New Methods Needs Proper Evaluation-Benchmarking Sets for Machine Learning Experiments for Class A GPCRs.

New computational approaches for virtual screening applications are constantly being developed. Howe...

Automated content analysis across six languages.

Corpus selection bias in international relations research presents an epistemological problem: How d...

Generative adversarial networks with mixture of t-distributions noise for diverse image generation.

Image generation is a long-standing problem in the machine learning and computer vision areas. In or...

Cooperation with autonomous machines through culture and emotion.

As machines that act autonomously on behalf of others-e.g., robots-become integral to society, it is...

Machine learning algorithm validation with a limited sample size.

Advances in neuroimaging, genomic, motion tracking, eye-tracking and many other technology-based dat...

Harnessing behavioral diversity to understand neural computations for cognition.

With the increasing acquisition of large-scale neural recordings comes the challenge of inferring th...

The black sheep effect: The case of the deviant ingroup robot.

The black sheep effect (BSE) describes the evaluative upgrading of norm-compliant group members (ing...

Artificial neural network model to predict transport parameters of reactive solutes from basic soil properties.

Measurement of solute-transport parameters through soils for a wide range of solute- and soil-types ...

Clinical applications of artificial intelligence in sepsis: A narrative review.

Many studies have been published on a variety of clinical applications of artificial intelligence (A...

Artificial intelligence reveals environmental constraints on colour diversity in insects.

Explaining colour variation among animals at broad geographic scales remains challenging. Here we de...

Artificially intelligent scoring and classification engine for forensic identification.

Despite advances in genotyping technologies, traditional kinship analysis tools utilized in forensic...

Unsupervised machine learning using an imaging mass spectrometry dataset automatically reassembles grey and white matter.

Current histological and anatomical analysis techniques, including fluorescence in situ hybridisatio...

Investigation of bias in an epilepsy machine learning algorithm trained on physician notes.

Racial disparities in the utilization of epilepsy surgery are well documented, but it is unknown whe...

Prediction of Potential Drug-Disease Associations through Deep Integration of Diversity and Projections of Various Drug Features.

Identifying new indications for existing drugs may reduce costs and expedites drug development. Drug...

An investigation of quantitative accuracy for deep learning based denoising in oncological PET.

Reducing radiation dose is important for PET imaging. However, reducing injection doses causes incre...

Hidden bias in the DUD-E dataset leads to misleading performance of deep learning in structure-based virtual screening.

Recently much effort has been invested in using convolutional neural network (CNN) models trained on...

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