人工智能
计算机科学
机器学习
深度学习
领域(数学)
学习迁移
特征提取
特征(语言学)
语言学
哲学
数学
纯数学
作者
Afiya Parveen Begum,Prabha Selvaraj
标识
DOI:10.1142/s0219467824500311
摘要
Alzheimer’s disease (AD) is a popular neurological disorder affecting a critical part of the world’s population. Its early diagnosis is extremely imperative for enhancing the quality of patients’ lives. Recently, improved technologies like image processing, artificial intelligence involving machine learning, deep learning, and transfer learning have been introduced for detecting AD. This review describes the contribution of image processing, feature extraction, optimization, and classification approach in AD recognition. It deeply investigates different methods adopted for multiclass diagnosis of AD. The paper further presents a brief comparison of existing AD studies in terms of techniques adopted, performance measures, classification accuracy, publication year, and datasets. It then summarizes the important technical barriers in reviewed works. This paper allows the readers to gain profound knowledge regarding AD diagnosis for promoting extensive research in this field.
科研通智能强力驱动
Strongly Powered by AbleSci AI