A comprehensive analysis of artificial intelligence techniques for the prediction and prognosis of lifestyle diseases

K Modi, I Singh, Y Kumar - Archives of Computational Methods in …, 2023 - Springer
Artificial intelligence is the fastest growing data-driven technology and is currently used in all
major fields and reduces the work of humans. Artificial intelligence can analyse extensive …

An analysis of detection and diagnosis of different classes of skin diseases using artificial intelligence-based learning approaches with hyper parameters

J Singh, JK Sandhu, Y Kumar - Archives of Computational Methods in …, 2024 - Springer
In recent years, metaheuristic optimizers have grown in popularity due to their ability to
efficiently optimize complex, high-dimensional problems that are difficult to solve using …

An analysis of deep transfer learning-based approaches for prediction and prognosis of multiple respiratory diseases using pulmonary images

A Koul, RK Bawa, Y Kumar - Archives of Computational Methods in …, 2024 - Springer
Respiratory diseases can lead to lung failure, which happens when the lungs cannot give
the body enough oxygen. These diseases can be diagnosed using medical data, lung …

A comprehensive analysis of deep learning-based approaches for prediction and prognosis of infectious diseases

K Thakur, M Kaur, Y Kumar - Archives of Computational Methods in …, 2023 - Springer
Artificial intelligence is the most powerful and promising tool for the present analytic
technologies. It can provide real-time insights into disease spread and predict new …

A comprehensive analysis of deep learning-based approaches for the prediction of gastrointestinal diseases using multi-class endoscopy images

P Bhardwaj, S Kumar, Y Kumar - Archives of Computational Methods in …, 2023 - Springer
The human gastrointestinal (GI) system can be affected by various illnesses which results in
the death of about two million patients globally. Endoscopy helps to detect such diseases as …

Machine learning-driven task scheduling with dynamic K-means based clustering algorithm using fuzzy logic in FOG environment

MS Sheikh, RN Enam, RI Qureshi - Frontiers in Computer Science, 2023 - frontiersin.org
Fog Computing has emerged as a pivotal technology for enabling low-latency, context-
aware, and efficient computing at the edge of the network. Effective task scheduling plays a …

Predictive modeling of nitrogen and phosphorus concentrations in rivers using a machine learning framework: A case study in an urban-rural transitional area in …

J Xue, C Yuan, X Ji, M Zhang - Science of the Total Environment, 2024 - Elsevier
Rapid urbanization in China since 1980 generated environmental pressures of non-point
source pollution (NPSP) and increased wide public concerns. Excessive quantities of …

A comprehensive analysis of hypertension disease risk-factors, diagnostics, and detections using deep learning-based approaches

S Kaur, K Bansal, Y Kumar, A Changela - Archives of Computational …, 2024 - Springer
High blood pressure, often known as hypertension, is a common and possibly fatal disorder
that affects a large section of the world's population. For complications to be avoided and the …

Machine‐Learning‐Driven G‐Quartet‐Based Circularly Polarized Luminescence Materials

Y Dai, Z Zhang, D Wang, T Li, Y Ren… - Advanced …, 2024 - Wiley Online Library
Circularly polarized luminescence (CPL) materials have garnered significant interest due to
their potential applications in chiral functional devices. Synthesizing CPL materials with a …

Application of Machine Learning approach on Halal meat authentication principle, challenges, and prospects: A Review

A Mustapha, I Ishak, NNM Zaki, MR Ismail-Fitry… - Heliyon, 2024 - cell.com
Meat is a source of essential amino acids that are necessary for human growth and
development, meat can come from dead, alive, Halal, or non-Halal animal species which are …