AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Eye Movements

Showing 11 to 20 of 133 articles

Clear Filters

AI can see you: Machiavellianism and extraversion are reflected in eye-movements.

PloS one
INTRODUCTION: Recent studies showed an association between personality traits and individual patterns of visual behaviour in laboratory and other settings. The current study extends previous research by measuring multiple personality traits in natura...

User Evaluation of a Shared Robot Control System Combining BCI and Eye Tracking in a Portable Augmented Reality User Interface.

Sensors (Basel, Switzerland)
This study evaluates an innovative control approach to assistive robotics by integrating brain-computer interface (BCI) technology and eye tracking into a shared control system for a mobile augmented reality user interface. Aimed at enhancing the aut...

Auxiliary diagnostic method of Parkinson's disease based on eye movement analysis in a virtual reality environment.

Neuroscience letters
Eye movement dysfunction is one of the non-motor symptoms of Parkinson's disease (PD). An accurate analysis method for eye movement is an effective way to gain a deeper understanding of the nervous system function of PD patients. However, currently, ...

The use of machine learning to understand the role of visual attention in multi-attribute choice.

Acta psychologica
Whether eye movements (as a measure of visual attention) contribute to the understanding of how multi-attribute decisions are made, is still a matter of debate. In this study, we show how machine learning methods can be used to separate the effects o...

Decoding Continuous Tracking Eye Movements from Cortical Spiking Activity.

International journal of neural systems
Eye movements are the primary way primates interact with the world. Understanding how the brain controls the eyes is therefore crucial for improving human health and designing visual rehabilitation devices. However, brain activity is challenging to d...

Inverting Cognitive Models With Neural Networks to Infer Preferences From Fixations.

Cognitive science
Inferring an individual's preferences from their observable behavior is a key step in the development of assistive decision-making technology. Although machine learning models such as neural networks could in principle be deployed toward this inferen...

Developing an AI-Based clinical decision support system for basal insulin titration in type 2 diabetes in primary Care: A Mixed-Methods evaluation using heuristic Analysis, user Feedback, and eye tracking.

International journal of medical informatics
BACKGROUND AND AIM: The progressive nature of type 2 diabetes often, in time, necessitates basal insulin therapy to achieve glycemic targets. However, despite standardized titration algorithms, many people remain poorly controlled after initiating in...

Enhancing Autism Detection Through Gaze Analysis Using Eye Tracking Sensors and Data Attribution with Distillation in Deep Neural Networks.

Sensors (Basel, Switzerland)
Autism Spectrum Disorder (ASD) is a neurodevelopmental condition characterized by differences in social communication and repetitive behaviors, often associated with atypical visual attention patterns. In this paper, the Gaze-Based Autism Classifier ...

Discrimination of Radiologists' Experience Level Using Eye-Tracking Technology and Machine Learning: Case Study.

JMIR formative research
BACKGROUND: Perception-related errors comprise most diagnostic mistakes in radiology. To mitigate this problem, radiologists use personalized and high-dimensional visual search strategies, otherwise known as search patterns. Qualitative descriptions ...

Towards the automatic detection of activities of daily living using eye-movement and accelerometer data with neural networks.

Computers in biology and medicine
Early diagnosis of neurodegenerative diseases, such as Alzheimer's disease, improves treatment and care outcomes for patients. Early signs of cognitive decline can be detected using functional scales, which are written records completed by a clinicia...