AIMC Topic: Humans

Clear Filters Showing 52351 to 52360 of 95995 articles

A minimal model of the interaction of social and individual learning.

Journal of theoretical biology
Learning is thought to be achieved by the selective, activity dependent, adjustment of synaptic connections. Individual learning can also be very hard and/or slow. Social, supervised, learning from others might amplify individual, possibly mainly uns...

Why human factors science is demonstrably necessary: historical and evolutionary foundations.

Ergonomics
We review the theoretical foundation for the need for human factors science. Over the past 2.8 million years, humans and tools have co-evolved. However, in the last century, technology is introduced at a rate that exceeds human evolution. The prolife...

Assessing the rate of aging to monitor aging itself.

Ageing research reviews
Healthy aging is the prime goal of aging research and interventions. Healthy aging or not can be quantified by biological aging rates estimated by aging clocks. Generation and accumulation of large scale high-dimensional biological data together with...

Artificial intelligence in neurodegenerative diseases: A review of available tools with a focus on machine learning techniques.

Artificial intelligence in medicine
Neurodegenerative diseases have shown an increasing incidence in the older population in recent years. A significant amount of research has been conducted to characterize these diseases. Computational methods, and particularly machine learning techni...

Discrepancies in Stroke Distribution and Dataset Origin in Machine Learning for Stroke.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
BACKGROUND: Machine learning algorithms depend on accurate and representative datasets for training in order to become valuable clinical tools that are widely generalizable to a varied population. We aim to conduct a review of machine learning uses i...

Machine learning in clinical decision making.

Med (New York, N.Y.)
Machine learning is increasingly integrated into clinical practice, with applications ranging from pre-clinical data processing, bedside diagnosis assistance, patient stratification, treatment decision making, and early warning as part of primary and...

Q-CHAT-NAO: A robotic approach to autism screening in toddlers.

Journal of biomedical informatics
The use of humanoid robots as assistants in therapy processes is not new. Several projects in the past several years have achieved promising results when combining human-robot interaction with standard techniques. Moreover, there are multiple screeni...

"Keep it simple, scholar": an experimental analysis of few-parameter segmentation networks for retinal vessels in fundus imaging.

International journal of computer assisted radiology and surgery
PURPOSE: With the recent development of deep learning technologies, various neural networks have been proposed for fundus retinal vessel segmentation. Among them, the U-Net is regarded as one of the most successful architectures. In this work, we sta...

Improvement of image quality for pancreatic cancer using deep learning-generated virtual monochromatic images: Comparison with single-energy computed tomography.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
PURPOSE: To construct a deep convolutional neural network that generates virtual monochromatic images (VMIs) from single-energy computed tomography (SECT) images for improved pancreatic cancer imaging quality.