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Influence of Reaction Time in the Emotional Response of a Companion Robot to a Child’s Aggressive Interaction
(
springer link
, 2020 , Article)
The quality of a companion robot’s reaction is important to make it acceptable to the users and to sustain interactions. Furthermore, the robot’s reaction can be used to train socially acceptable behaviors and to develop ...
Using artificial intelligence to improve body iron quantification: A scoping review
(
Elsevier
, 2023 , Article Review)
This scoping review explores the potential of artificial intelligence (AI) in enhancing the screening, diagnosis, and monitoring of disorders related to body iron levels. A systematic search was performed to identify studies ...
Audio-Based Drone Detection and Identification Using Deep Learning Techniques with Dataset Enhancement through Generative Adversarial Networks
(
MDPI
, 2021 , Article)
Drones are becoming increasingly popular not only for recreational purposes but in day-to-day applications in engineering, medicine, logistics, security and others. In addition to their useful applications, an alarming ...
Artificial intelligence in sickle disease
(
Churchill Livingstone
, 2023 , Article Review)
Artificial intelligence (AI) is rapidly becoming an established arm in medical sciences and clinical practice in numerous medical fields. Its implications have been rising and are being widely used in research, diagnostics, ...
Exploration and analysis of On-Surface and In-Air handwriting attributes to improve dysgraphia disorder diagnosis in children based on machine learning methods
(
Elsevier
, 2023 , Article)
Dysgraphia is a type of learning disorder that affects children’s writing skills. Poor writing skills can obstruct students’ academic growth if it is undiagnosed and untreated properly in the early stages. The irregularity ...
Revolutionizing chronic lymphocytic leukemia diagnosis: A deep dive into the diverse applications of machine learning
(
Elsevier
, 2023 , Article)
Chronic lymphocytic leukemia (CLL) is a B cell neoplasm characterized by the accumulation of aberrant monoclonal B lymphocytes. CLL is the predominant type of leukemia in Western countries, accounting for 25% of cases. ...
Machine learning techniques for the identification of risk factors associated with food insecurity among adults in Arab countries during the COVID-19 pandemic
(
Springer Nature
, 2023 , Article)
Background: A direct consequence of global warming, and strongly correlated with poor physical and mental health, food insecurity is a rising global concern associated with low dietary intake. The Coronavirus pandemic has ...
A machine learning-based optimization approach for pre-copy live virtual machine migration
(
Springer
, 2023 , Article)
Organizations widely use cloud computing to outsource their computing needs. One crucial issue of cloud computing is that services must be available to clients at all times. However, the cloud services may be temporarily ...
Performance of artificial intelligence models in estimating blood glucose level among diabetic patients using non-invasive wearable device data
(
Elsevier
, 2023 , Article)
Introduction: Diabetes Mellitus (DM) is characterized by impaired ability to metabolize glucose for use in cells for energy, resulting in high blood sugar (hyperglycemia). DM impacted 463 million individuals worldwide in ...
Development of a stacked machine learning model to compute the capability of ZnO-based sensors for hydrogen detection
(
Elsevier
, 2024 , Article)
Zinc oxide (ZnO) nanocomposite sensors decorated with various dopants are popular tools for detecting even low hydrogen (H2) concentrations. The nanocomposite's chemistry, temperature, and H2 concentration impact the success ...