AIMC Topic: Humans

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Augmented Analytics Driven by AI: A Digital Transformation beyond Business Intelligence.

Sensors (Basel, Switzerland)
Lately, Augmented Analytics (AA) has increasingly been introduced as a tool for transforming data into valuable insights for decision-making, and it has gained attention as one of the most advanced methods to facilitate modern analytics for different...

A Survey on Medical Explainable AI (XAI): Recent Progress, Explainability Approach, Human Interaction and Scoring System.

Sensors (Basel, Switzerland)
The emerging field of eXplainable AI (XAI) in the medical domain is considered to be of utmost importance. Meanwhile, incorporating explanations in the medical domain with respect to legal and ethical AI is necessary to understand detailed decisions,...

Kids' Emotion Recognition Using Various Deep-Learning Models with Explainable AI.

Sensors (Basel, Switzerland)
Human ideas and sentiments are mirrored in facial expressions. They give the spectator a plethora of social cues, such as the viewer's focus of attention, intention, motivation, and mood, which can help develop better interactive solutions in online ...

Matched Filter Interpretation of CNN Classifiers with Application to HAR.

Sensors (Basel, Switzerland)
Time series classification is an active research topic due to its wide range of applications and the proliferation of sensory data. Convolutional neural networks (CNNs) are ubiquitous in modern machine learning (ML) models. In this work, we present a...

Experimental Comparison of Biofidel Measuring Devices Used for the Validation of Collaborative Robotics Applications.

International journal of environmental research and public health
Biofidel measuring devices are used to validate safety in collaborative workplaces. In these workplaces, humans work together with robots that are equipped with a Power and Force Limiting function (PFL). In this experimental comparison, differences b...

Deep learning diagnostics for bladder tumor identification and grade prediction using RGB method.

Scientific reports
We evaluate the diagnostic performance of deep learning artificial intelligence (AI) for bladder cancer, which used white-light images (WLIs) and narrow-band images, and tumor grade prediction of AI based on tumor color using the red/green/blue (RGB)...

Input feature design and its impact on the performance of deep learning models for predicting fluence maps in intensity-modulated radiation therapy.

Physics in medicine and biology
. Deep learning (DL) models for fluence map prediction (FMP) have great potential to reduce treatment planning time in intensity-modulated radiation therapy (IMRT) by avoiding the lengthy inverse optimization process. This study aims to improve the r...

SFA-Net: Scale and Feature Aggregate Network for Retinal Vessel Segmentation.

Journal of healthcare engineering
A U-Net-based network has achieved competitive performance in retinal vessel segmentation. Previous work has focused on using multilevel high-level features to improve segmentation accuracy but has ignored the importance of shallow-level features. In...

Misplaced Trust and Distrust: How Not to Engage with Medical Artificial Intelligence.

Cambridge quarterly of healthcare ethics : CQ : the international journal of healthcare ethics committees
Artificial intelligence (AI) plays a rapidly increasing role in clinical care. Many of these systems, for instance, deep learning-based applications using multilayered Artificial Neural Nets, exhibit epistemic opacity in the sense that they preclude ...

Robotic applications for intracardiac and endovascular procedures.

Trends in cardiovascular medicine
The large incisions and long recovery periods that accompany traditional cardiac surgery procedures along with the constant patient demand for minimally invasive procedures have motivated cardiac surgeons to implement the robotic technologies in thei...