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Now showing items 121-130 of 130
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 ...
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 ...
Use of machine learning to assess factors affecting progression, retention, and graduation in first-year health professions students in Qatar: a longitudinal study
(
BioMed Central Ltd
, 2023 , Article)
Background: Across higher education, student retention, progression, and graduation are considered essential elements of students’ academic success. However, there is scarce literature analyzing these attributes across ...
Analysis of Unsupervised Consumption Anomaly Detection in Sports Facilities using Artificial Intelligence-Based Data Analytics: A Case Study
(
Association for Computing Machinery (ACM)
, 2023 , Conference Paper)
Sports facilities have exceptionally high energy demand due to the extensive operational requirements and high-occupancy seasonal rates. Towards promoting efficient energy usage and minimal losses, consumption anomaly ...
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 ...
Modeling of permeability impairment dynamics in porous media: A machine learning approach
(
Elsevier
, 2023 , Article)
The prediction of clogging and permeability impairment dynamics in porous media is crucial for the optimization of various industrial and natural processes. This paper presents a novel machine learning-based approach for ...
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 ...
Estimating Blood Glucose Levels Using Machine Learning Models with Non-Invasive Wearable Device Data
(
IOS Press BV
, 2023 , Conference Paper)
In 2019 alone, Diabetes Mellitus impacted 463 million individuals worldwide. Blood glucose levels (BGL) are often monitored via invasive techniques as part of routine protocols. Recently, AI-based approaches have shown the ...
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 ...