Guest Editorial Advanced Machine Learning Algorithms for Biomedical Data and Imaging

被引:2
作者
Tanveer, M. [1 ]
Lin, Chin-Teng [2 ]
Kumar Singh, Amit [3 ]
机构
[1] Indian Inst Technol Indore, Discipline Math, Simrol 453552, India
[2] Univ Technol Sydney, Fac Engn & Informat Technol, Australian Artificial Intelligence Inst, Ultimo, NSW 2007, Australia
[3] Natl Inst Technol Patna, Comp Sci & Engn Dept, Patna 800005, Bihar, India
关键词
Special issues and sections; Machine learning; Informatics; Bioinformatics; Biomedical image processing; Feature extraction; Brain modeling; Electroencephalography; Electrocardiography; Hidden Markov models; Medical diagnostic imaging;
D O I
10.1109/JBHI.2022.3204385
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The papers in this special section focus on advanced machine learning algorithms for biomedical data and image processing. Researchers in machine learning including those working in computer vision, image processing, biomedical analysis, and related fields when tied with experienced clinicians can play a significant role in understanding and working on complex medical data which ultimately improves patient care. Developing a novel machine-learning algorithm specific to medical data is a challenge and need of the hour. Healthcare and biomedical sciences have become data-intensive fields, with a strong need for sophisticated data mining methods to extract the knowledge from the available information. Biomedical data contains several challenges in data analysis, including high dimensionality, class imbalance, and low numbers of samples. Although the current research in this field has shown promising results, several research issues need to be explored as follows. There is a need to explore novel feature selection methods to improve predictive performance along with interpretation and to explore large-scale data in biomedical sciences.
引用
收藏
页码:4809 / 4813
页数:5
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