AIMC Topic: Humans

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The Impact of Artificial Intelligence on Data System Security: A Literature Review.

Sensors (Basel, Switzerland)
Diverse forms of artificial intelligence (AI) are at the forefront of triggering digital security innovations based on the threats that are arising in this post-COVID world. On the one hand, companies are experiencing difficulty in dealing with secur...

A qualitative exploration of care homes workers' views and training needs in relation to the use of socially assistive humanoid robots in their workplace.

International journal of older people nursing
AIM: The study aimed to explore the views and attitudes of care home workers about the socially assistive robot that was trialled in their workplace, in order to identify training needs in relation to the hypothetical future use of these robots in th...

The Potential Cost-Effectiveness of a Machine Learning Tool That Can Prevent Untimely Intensive Care Unit Discharge.

Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research
OBJECTIVES: The machine learning prediction model Pacmed Critical (PC), currently under development, may guide intensivists in their decision-making process on the most appropriate time to discharge a patient from the intensive care unit (ICU). Given...

A parallel attention-augmented bilinear network for early magnetic resonance imaging-based diagnosis of Alzheimer's disease.

Human brain mapping
Structural magnetic resonance imaging (sMRI) can capture the spatial patterns of brain atrophy in Alzheimer's disease (AD) and incipient dementia. Recently, many sMRI-based deep learning methods have been developed for AD diagnosis. Some of these met...

One-dimensional convolutional neural network and hybrid deep-learning paradigm for classification of specific language impaired children using their speech.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Screening children for communicational disorders such as specific language impairment (SLI) is always challenging as it requires clinicians to follow a series of steps to evaluate the subjects. Artificial intelligence and co...

A multi-scale unsupervised learning for deformable image registration.

International journal of computer assisted radiology and surgery
PURPOSE: Image registration is a fundamental task in the area of image processing, and it is critical to many clinical applications, e.g., computer-assisted surgery. In this work, we attempt to design an effective framework that gains higher accuracy...

A community effort to assess and improve computerized interpretation of 12-lead resting electrocardiogram.

Medical & biological engineering & computing
Computerized interpretation of electrocardiogram plays an important role in daily cardiovascular healthcare. However, inaccurate interpretations lead to misdiagnoses and delay proper treatments. In this work, we built a high-quality Chinese 12-lead r...

AI Integration in the Clinical Workflow.

Journal of digital imaging
Machine learning and artificial intelligence (AI) algorithms hold significant promise for addressing important clinical needs when applied to medical imaging; however, integration of algorithms into a radiology department is challenging. Vended algor...

Can Deep Learning-Based Volumetric Analysis Predict Oxygen Demand Increase in Patients with COVID-19 Pneumonia?

Medicina (Kaunas, Lithuania)
: This study aimed to investigate whether predictive indicators for the deterioration of respiratory status can be derived from the deep learning data analysis of initial chest computed tomography (CT) scans of patients with coronavirus disease 2019 ...

A Deep Learning-Based Intrusion Detection System for MQTT Enabled IoT.

Sensors (Basel, Switzerland)
A large number of smart devices in Internet of Things (IoT) environments communicate via different messaging protocols. Message Queuing Telemetry Transport (MQTT) is a widely used publish-subscribe-based protocol for the communication of sensor or ev...