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

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Explainable artificial intelligence for reliable water demand forecasting to increase trust in predictions.

The "EU Artificial Intelligence Act" sets a framework for the implementation of artificial intellige...

Testing process for artificial intelligence applications in radiology practice.

Artificial intelligence (AI) applications are becoming increasingly common in radiology. However, en...

Statistical inference and neural network training based on stochastic difference model for air pollution and associated disease transmission.

A polluted air environment can potentially provoke infections of diverse respiratory diseases. The d...

Development and validation of a prediction model for ED using machine learning: according to NHANES 2001-2004.

Erectile Dysfunction (ED) is a form of sexual dysfunction in males that imposes significant health a...

Bias Sensitivity in Diagnostic Decision-Making: Comparing ChatGPT with Residents.

BACKGROUND: Diagnostic errors, often due to biases in clinical reasoning, significantly affect patie...

Interaction-Based Inductive Bias in Graph Neural Networks: Enhancing Protein-Ligand Binding Affinity Predictions From 3D Structures.

Inductive bias in machine learning (ML) is the set of assumptions describing how a model makes predi...

Feature Selection and Machine Learning Approaches in Prediction of Current E-Cigarette Use Among U.S. Adults in 2022.

Feature selection is essentially the process of picking informative and relevant features from a lar...

Machine learning model for age-related macular degeneration based on heavy metals: The National Health and Nutrition Examination Survey 2005 to 2008.

Age-related macular degeneration (AMD) is the leading cause of blindness in older people in develope...

AmbiBias Contrast: Enhancing debiasing networks via disentangled space from ambiguity-bias clusters.

The goal of debiasing in classification tasks is to train models to be less sensitive to correlation...

Knowledge-based inductive bias and domain adaptation for cell type annotation.

Measurement techniques often result in domain gaps among batches of cellular data from a specific mo...

Misidentifications in ayurvedic medicinal plants: Convolutional neural network (CNN) to overcome identification confusions.

Plants are a vital ingredient of traditional medicine in Sri Lanka, and the quantity of medicinal pl...

Evaluating machine learning model bias and racial disparities in non-small cell lung cancer using SEER registry data.

BACKGROUND: Despite decades of pursuing health equity, racial and ethnic disparities persist in heal...

The Potential of Artificial Intelligence Tools for Reducing Uncertainty in Medicine and Directions for Medical Education.

In the field of medicine, uncertainty is inherent. Physicians are asked to make decisions on a daily...

The bias algorithm: how AI in healthcare exacerbates ethnic and racial disparities - a scoping review.

This scoping review examined racial and ethnic bias in artificial intelligence health algorithms (AI...

Design of a Trustworthy Cloud-Native National Digital Health Information Infrastructure for Secure Data Management and Use.

Since 2022, Malawi Ministry of Health (MoH) designated the development of a National Digital Health ...

GradToken: Decoupling tokens with class-aware gradient for visual explanation of Transformer network.

Transformer networks have been widely used in the fields of computer vision, natural language proces...

A survey on representation learning for multi-view data.

Multi-view clustering has become a rapidly growing field in machine learning and data mining areas b...

Use of Artificial Intelligence in Cobb Angle Measurement for Scoliosis: Retrospective Reliability and Accuracy Study of a Mobile App.

BACKGROUND: Scoliosis is a spinal deformity in which one or more spinal segments bend to the side or...

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