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Automatic monitoring system for individual dairy cows based on a deep learning framework that provides identification via body parts and estimation of body condition score.

Journal of dairy science
Body condition score (BCS) is a common tool for indirectly estimating the mobilization of energy reserves in the fat and muscle of cattle that meets the requirements of animal welfare and precision livestock farming for the effective monitoring of in...

Using supervised learning machine algorithm to identify future fallers based on gait patterns: A two-year longitudinal study.

Experimental gerontology
INTRODUCTION: Given their major health consequences in the elderly, identifying people at risk of fall is a major challenge faced by clinicians. A lot of studies have confirmed the relationships between gait parameters and falls incidence. However, a...

Human decision-making biases in the moral dilemmas of autonomous vehicles.

Scientific reports
The development of artificial intelligence has led researchers to study the ethical principles that should guide machine behavior. The challenge in building machine morality based on people's moral decisions, however, is accounting for the biases in ...

Automated Muscle Segmentation from Clinical CT Using Bayesian U-Net for Personalized Musculoskeletal Modeling.

IEEE transactions on medical imaging
We propose a method for automatic segmentation of individual muscles from a clinical CT. The method uses Bayesian convolutional neural networks with the U-Net architecture, using Monte Carlo dropout that infers an uncertainty metric in addition to th...

What do patients learn about psychotropic medications on the web? A natural language processing study.

Journal of affective disorders
BACKGROUND: Low rates of medication adherence remain a major challenge across psychiatry. In part, this likely reflects patient concerns about safety and adverse effects, accurate or otherwise. We therefore sought to characterize online information a...

Quantifying brain metabolism from FDG-PET images into a probability of Alzheimer's dementia score.

Human brain mapping
F-fluorodeoxyglucose positron emission tomography (FDG-PET) enables in-vivo capture of the topographic metabolism patterns in the brain. These images have shown great promise in revealing the altered metabolism patterns in Alzheimer's disease (AD). ...

PTSD and its dissociative subtype through the lens of the insula: Anterior and posterior insula resting-state functional connectivity and its predictive validity using machine learning.

Psychophysiology
Individuals with post-traumatic stress disorder (PTSD) typically experience states of reliving and hypervigilance; however, the dissociative subtype of PTSD (PTSD+DS) presents with additional symptoms of depersonalization and derealization. Although ...

Injecting and removing suspicious features in breast imaging with CycleGAN: A pilot study of automated adversarial attacks using neural networks on small images.

European journal of radiology
PURPOSE: To train a CycleGAN on downscaled versions of mammographic data to artificially inject or remove suspicious features, and to determine whether these AI-mediated attacks can be detected by radiologists.

Development and accuracy of an artificial intelligence algorithm for acne grading from smartphone photographs.

Experimental dermatology
We developed an artificial intelligence algorithm (AIA) for smartphones to determine the severity of facial acne using the GEA scale and to identify different types of acne lesion (comedonal, inflammatory) and postinflammatory hyperpigmentation (PIHP...