Journal of Artificial Intelligence Research & Advances
Volume 9, Issue 2 (2022)
Published
Table of contents
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Implementation of Data Mining Approach to Find the Adaptability of Students in Online Education During COVID-19 Pandemic
Abstract: The global COVID-19 pandemic has severely affected every aspect of human life, including education. The virus' stunning spread created havoc in the educational system, causing educational institutions to close. As an effect, students must quickly adopt to the change to synchronous online learning. This study identified the different aspects affecting the adaptability level of students in online class. It also identifies the student’s adaptability level in different circumstances in online …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 9, Issue 2, 2022 · pp. 1–8 Read article
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Hybrid Authentication Scheme Based on Cyber Physical System Use in Agriculture
Abstract: Recently, the agriculture industry has seen the application of artificial intelligence (AI). To maximize yield, the industry must overcome a number of obstacles, including poor soil management, infection by pests and pathogens, the need for huge information, low output, and a technological lack of clarity among farm owners. The core principles of intelligence in farmland are expense, precision, good speed, and scalability. This study reviews the various applications of artificial …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 9, Issue 2, 2022 · pp. 25–36 Read article
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Timely Diabetes Possibility Prediction Using AI Techniques
Abstract: The fastest chronic life-threatening disease affecting more than 422 million people globally is diabetes. The primary causes of type 2 diabetes are lifestyle choices and environmental factors. It is a slowgrowing disease which starts to develop metabolic factors long before they evolve into a disease and is formally diagnosed by a fasting sugar test. There are records of indications related to diabetes from 520 patients in the dataset that was …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 9, Issue 2, 2022 · pp. 37–47 Read article
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Hybrid Feature Selection Approach for Stability Prediction for Intracerebral Hemorrhage Patients
Abstract: Intra Cerebral Hemorrhage (ICH) stability estimation is useful for enhancing diagnosis accuracy, selecting the best course of treatment, and clinically evaluating variations with healthy individuals. Due to their low predictive value, the clinical application of several ICH progression scoring systems is constrained. The dataset includes clinical parameters including age, Glasgow Coma Scale (GCS), and CT Angiography (CTA) spot that have been retrieved using geometric features from the segmented bleeding volume …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 9, Issue 2, 2022 · pp. 9–17 Read article