The main objective of feature selection is to improve learning performance by selecting
concise and informative feature subsets, which presents a challenging task for machine …

Abstract Arithmetic Optimization Algorithm (AOA) is a recently developed population-based
nature-inspired optimization algorithm (NIOA). AOA is designed under the inspiration of the …

Abstract Feature Subset Selection (FSS) is an NP-hard problem to remove redundant and
irrelevant features particularly from medical data, and it can be effectively addressed by …

Arithmetic optimization algorithm (AOA) is a math optimizer proposed to solve optimization
challenges. Its capability to find the global solution comes from the behavior of four …

In this paper, we study the applications of metaheuristics (MH) optimization algorithms in
human activity recognition (HAR) and fall detection based on sensor data. It is known that …

Bone malignant tumors are metastatic and aggressive, with poor treatment outcomes and
prognosis. Rapid and accurate diagnosis is crucial for limb salvage and increasing the …

One of the most prevalent malignant bone tumors is osteosarcoma. The diagnosis and
treatment cycle are long and the prognosis is poor. It takes a lot of time to manually identify …

Gene expression data play a significant role in the development of effective cancer
diagnosis and prognosis techniques. However, many redundant, noisy, and irrelevant genes …

Medical image analysis methods have been applied to clinical scenarios of tumor diagnosis
and treatment. Many studies have attempted to optimize the effectiveness of tumor MRI …

Simple Summary Osteosarcoma is a rare form of bone cancer that primarily affects children
and adolescents during their growth years. Known to be one of the most aggressive tumors …