AIMC Topic: Humans

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Feature Fusion of a Deep-Learning Algorithm into Wearable Sensor Devices for Human Activity Recognition.

Sensors (Basel, Switzerland)
This paper presents a wearable device, fitted on the waist of a participant that recognizes six activities of daily living (walking, walking upstairs, walking downstairs, sitting, standing, and laying) through a deep-learning algorithm, human activit...

Abnormal Activity Recognition from Surveillance Videos Using Convolutional Neural Network.

Sensors (Basel, Switzerland)
UNLABELLED: Background and motivation: Every year, millions of Muslims worldwide come to Mecca to perform the Hajj. In order to maintain the security of the pilgrims, the Saudi government has installed about 5000 closed circuit television (CCTV) came...

Towards a Resilience to Stress Index Based on Physiological Response: A Machine Learning Approach.

Sensors (Basel, Switzerland)
This study proposes a new index to measure the resilience of an individual to stress, based on the changes of specific physiological variables. These variables include electromyography, which is the muscle response, blood volume pulse, breathing rate...

A systematic review of artificial intelligence chatbots for promoting physical activity, healthy diet, and weight loss.

The international journal of behavioral nutrition and physical activity
BACKGROUND: This systematic review aimed to evaluate AI chatbot characteristics, functions, and core conversational capacities and investigate whether AI chatbot interventions were effective in changing physical activity, healthy eating, weight manag...

Artificial Intelligence in Medicine: A Sword of Damocles?

Journal of medical systems
Will Artificial Intelligence (AI) re-humanize or de-humanize medicine? As AI becomes pervasive in clinical medicine, we argue that the ethical framework that sustains a responsible implementation of such technologies should be reconsidered. The emerg...

Automation of a Rule-based Workflow to Estimate Age from Brain MR Imaging of Infants and Children Up to 2 Years Old Using Stacked Deep Learning.

Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine
PURPOSE: Myelination-related MR signal changes in white matter are helpful for assessing normal development in infants and children. A rule-based myelination evaluation workflow regarding signal changes on T1-weighted images (T1WIs) and T2-weighted i...

Exploring the Black Box of Managing Total Rewards for Older Professionals in the Canadian Financial Services Sector.

Canadian journal on aging = La revue canadienne du vieillissement
This study extends our knowledge about the management of older employees in the sector of financial services, which faces enormous transformational pressures (e.g., emergence of artificial intelligence, digital services). Based on the black box model...

Trustworthy AI: Closing the gap between development and integration of AI systems in ophthalmic practice.

Progress in retinal and eye research
An increasing number of artificial intelligence (AI) systems are being proposed in ophthalmology, motivated by the variety and amount of clinical and imaging data, as well as their potential benefits at the different stages of patient care. Despite a...

Artificial intelligence in functional imaging of the lung.

The British journal of radiology
Artificial intelligence (AI) is transforming the way we perform advanced imaging. From high-resolution image reconstruction to predicting functional response from clinically acquired data, AI is promising to revolutionize clinical evaluation of lung ...

Machine learning models on chemical inhibitors of mitochondrial electron transport chain.

Journal of hazardous materials
Chemicals can induce adverse effects in humans by inhibiting mitochondrial electron transport chain (ETC) such as disrupting mitochondrial membrane potential, enhancing oxidative stress and causing some diseases. Thus, identifying ETC inhibitors (ETC...