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Evolution of artificial intelligence research in Technological Forecasting and Social Change: Research topics, trends, and future directions
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Elsevier
, 2023 , Article)
Artificial intelligence (AI) is a set of rapidly expanding disruptive technologies that are radically transforming various aspects related to people, business, society, and the environment. With the proliferation of digital ...
Protein glycation – biomarkers of metabolic dysfunction and early-stage decline in health in the era of precision medicine
(
Elsevier
, 2021 , Article)
Protein glycation provides a biomarker in widespread clinical use, glycated hemoglobin HbA1c (A1C). It is a biomarker for diagnosis of diabetes and prediabetes and of medium-term glycemic control in patients with established ...
Urban resilience and livability performance of European smart cities: A novel machine learning approach
(
Elsevier
, 2022 , Article)
Smart cities are centres of economic opulence and hope for standardized living. Understanding the shades of urban resilience and livability in smart city models is of paramount importance. This study presents a novel ...
State of charge estimation for a group of lithium-ion batteries using long short-term memory neural network
(
Elsevier
, 2022 , Article)
The present paper estimates for the first time the State of Charge (SoC) of a high capacity grid-scale lithium-ion battery storage system used to improve the power profile in a distribution network. The proposed long ...
Arabic natural language processing for Qur'anic research: a systematic review
(
Springer Nature
, 2023 , Article)
The Qur'an is a fourteen centuries old divine book in Arabic language that is read and followed by almost two billion Muslims globally as their sacred religious text. With the rise of Islam, the Arabic language gained ...
Methodological considerations for identifying multiple plasma proteins associated with all-cause mortality in a population-based prospective cohort
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Nature Research
, 2021 , Article)
Novel methods to characterize the plasma proteome has made it possible to examine a wide range of proteins in large longitudinal cohort studies, but the complexity of the human proteome makes it difficult to identify robust ...
The impact of COVID-19 pandemic on electricity consumption and electricity demand forecasting accuracy: Empirical evidence from the state of Qatar
(
Elsevier Ltd
, 2022 , Article)
The goal of this study is to use machine-learning (ML) techniques and empirical big data to examine the influence of the COVID-19 pandemic on electricity usage and electricity demand forecasting accuracy in buildings in ...
Use of machine learning to assess factors affecting progression, retention, and graduation in first-year health professions students in Qatar: a longitudinal study
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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 ...
CNN feature and classifier fusion on novel transformed image dataset for dysgraphia diagnosis in children
(
Elsevier
, 2023 , Article)
Dysgraphia is a neurological disorder that hinders the acquisition process of normal writing skills in children, resulting in poor writing abilities. Poor or underdeveloped writing skills in children can negatively impact ...
A new approach to predicting cryptocurrency returns based on the gold prices with support vector machines during the COVID-19 pandemic using sensor-related data
(
MDPI
, 2021 , Article)
In a real-world situation produced under COVID-19 scenarios, predicting cryptocurrency returns accurately can be challenging. Such a prediction may be helpful to the daily economic and financial market. Unlike forecasting ...