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Surveys

Latest AI and machine learning research in surveys for healthcare professionals.

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The anesthesiologist's guide to critically assessing machine learning research: a narrative review.

Artificial Intelligence (AI), especially Machine Learning (ML), has developed systems capable of per...

Unmasking the chameleons: A benchmark for out-of-distribution detection in medical tabular data.

BACKGROUND: Machine Learning (ML) models often struggle to generalize effectively to data that devia...

A Bias Network Approach (BNA) to Encourage Ethical Reflection Among AI Developers.

We introduce the Bias Network Approach (BNA) as a sociotechnical method for AI developers to identif...

Transformers deep learning models for missing data imputation: an application of the ReMasker model on a psychometric scale.

INTRODUCTION: Missing data in psychometric research presents a substantial challenge, impacting the ...

Policy brief: Improving national vaccination decision-making through data.

Life course immunisation looks at the broad value of vaccination across multiple generations, callin...

Ethical and Bias Considerations in Artificial Intelligence/Machine Learning.

As artificial intelligence (AI) gains prominence in pathology and medicine, the ethical implications...

Classification-Based Detection and Quantification of Cross-Domain Data Bias in Materials Discovery.

It stands to reason that the amount and the quality of data are of key importance for setting up acc...

Investigating Older Adults' Perceptions of AI Tools for Medication Decisions: Vignette-Based Experimental Survey.

BACKGROUND: Given the public release of large language models, research is needed to explore whether...

Improving WRF-Chem PM predictions by combining data assimilation and deep-learning-based bias correction.

In numerical model simulations, data assimilation (DA) on the initial conditions and bias correction...

Raising awareness may increase the likelihood of hematopoietic stem cell donation: a nationwide survey using artificial intelligence.

BACKGROUND: In Italy, the demand for allogeneic transplantation exceeds the number of compatible don...

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 comple...

A roadmap for improving data quality through standards for collaborative intelligence in human-robot applications.

Collaborative intelligence (CI) involves human-machine interactions and is deemed safety-critical be...

Dietary caffeine and its negative link to serum Klotho concentrations: evidence from the National Health and Nutrition Examination Survey.

BACKGROUND: This is the initial investigation assessing the association between caffeine consumption...

Deep Learning in Gene Regulatory Network Inference: A Survey.

Understanding the intricate regulatory relationships among genes is crucial for comprehending the de...

Diffusing on Two Levels and Optimizing for Multiple Properties: A Novel Approach to Generating Molecules With Desirable Properties.

In the past decade, Artificial Intelligence (AI) driven drug design and discovery has been a hot res...

Employing Machine Learning Techniques to Detect Protein Function: A Survey, Experimental, and Empirical Evaluations.

This review article delves deeply into the various machine learning (ML) methods and algorithms empl...

Evaluation of the clinical utility of lateral cephalometry reconstructed from computed tomography extracted by artificial intelligence.

This study assessed the accuracy and reliability of artificial intelligence (AI)-reconstructed image...

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