AIMC Topic: Humans

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A Robust Artificial Intelligence Approach with Explainability for Measurement and Verification of Energy Efficient Infrastructure for Net Zero Carbon Emissions.

Sensors (Basel, Switzerland)
Rapid urbanization across the world has led to an exponential increase in demand for utilities, electricity, gas and water. The building infrastructure sector is one of the largest global consumers of electricity and thereby one of the largest emitte...

An Integrated Artificial Intelligence of Things Environment for River Flood Prevention.

Sensors (Basel, Switzerland)
River floods are listed among the natural disasters that can directly influence different aspects of life, ranging from human lives, to economy, infrastructure, agriculture, etc. Organizations are investing heavily in research to find more efficient ...

The usability and feasibility validation of the social robot MINI in people with dementia and mild cognitive impairment; a study protocol.

BMC psychiatry
BACKGROUND: Social robots have demonstrated promising outcomes in terms of increasing the social health and well-being of people with dementia and mild cognitive impairment. According to the World Health Organization's Monitoring and assessing digita...

A fully-automated paper ECG digitisation algorithm using deep learning.

Scientific reports
There is increasing focus on applying deep learning methods to electrocardiograms (ECGs), with recent studies showing that neural networks (NNs) can predict future heart failure or atrial fibrillation from the ECG alone. However, large numbers of ECG...

Deep learning approaches to predict 10-2 visual field from wide-field swept-source optical coherence tomography en face images in glaucoma.

Scientific reports
Close monitoring of central visual field (VF) defects with 10-2 VF helps prevent blindness in glaucoma. We aimed to develop a deep learning model to predict 10-2 VF from wide-field swept-source optical coherence tomography (SS-OCT) images. Macular ga...

Machine-learning-based risk stratification for probability of dying in patients with basal ganglia hemorrhage.

Scientific reports
To confirm whether machine learning algorithms (MLA) can achieve an effective risk stratification of dying within 7 days after basal ganglia hemorrhage (BGH). We collected patients with BGH admitted to Sichuan Provincial People's Hospital between Aug...

Robot Technology for the Elderly and the Value of Veracity: Disruptive Technology or Reinvigorating Entrenched Principles?

Science and engineering ethics
The implementation of care robotics in care settings is identified by some authors as a disruptive innovation, in the sense that it will upend the praxis of care. It is an open ethical question whether this alleged disruption will also have a transfo...

Artificial intelligence in veterinary diagnostic imaging: A literature review.

Veterinary radiology & ultrasound : the official journal of the American College of Veterinary Radiology and the International Veterinary Radiology Association
Artificial intelligence in veterinary medicine is an emerging field. Machine learning, a subfield of artificial intelligence, allows computer programs to analyze large imaging datasets and learn to perform tasks relevant to veterinary diagnostic imag...

Risk Classification and Subphenotyping of Acute Kidney Injury: Concepts and Methodologies.

Seminars in nephrology
Acute kidney injury (AKI) is a complex syndrome with a paucity of therapeutic development. One aspect that could explain the lack of implementation science in the AKI field is the vast heterogeneity of the AKI syndrome, which hinders precise therapeu...