Journal of Healthcare Engineering

Machine Learning Theory and Applications for Healthcare


Status
Published

Lead Editor

1University of Allahabad, Allahabad, India

2Gwangju Institute of Science and Technology, Gwangju, Republic of Korea

3Oakland University, Rochester Hills, USA

4Changshu Institute of Technology, Changshu, China


Machine Learning Theory and Applications for Healthcare

Description

Machine learning has evolved from pattern recognition and computational learning theory in artificial intelligence, exploring the construction and study of algorithms that learn from data and make predictions. Machine learning is increasingly applied to healthcare, including medical image segmentation, image registration, multimodal image fusion, computer-aided diagnosis, image-guided therapy, image annotation, and image database retrieval, where failure could be fatal.

The purpose of this special issue is to advance scientific research in the broad field of machine learning in healthcare, with focuses on theory, applications, recent challenges, and cutting-edge techniques.

Machine learning techniques (e.g., support vector machines, statistical or mathematical methods, extreme learning machines, deep learning, artificial neural networks, evolutionary algorithms, multiobjective metaheuristics, learning through fuzzy logic, cooperative learning, multiagent learning, and planning) with their theory and applications to the following:

Potential topics include but are not limited to the following:

  • Biomedical signal and image processing
  • Multimodal information fusion
  • Mathematical and statistical models
  • Multivariate statistical analysis
  • Pattern recognition in biomedical applications
  • Advanced computer-aided detection/diagnosis
  • Advanced cellular image analysis
  • Advanced medical image (database) retrieval
  • Advanced medical image reconstruction
  • Advanced molecular/pathologic image analysis
  • Multimodal neurochemical and/or imaging biomarkers
  • Biometrics
  • Gait and motion analysis using complex biomedical signals
  • Brain computer interfacing
  • Clinical big data analytics
  • Assistive devices for elderly care and disabled people

Articles

  • Special Issue
  • - Volume 2017
  • - Article ID 5263570
  • - Editorial

Machine Learning Theory and Applications for Healthcare

Ashish Khare | Moongu Jeon | ... | Benlian Xu
  • Special Issue
  • - Volume 2017
  • - Article ID 8750506
  • - Research Article

Twin SVM-Based Classification of Alzheimer’s Disease Using Complex Dual-Tree Wavelet Principal Coefficients and LDA

Saruar Alam | Goo-Rak Kwon | ... | Chun-Su Park
  • Special Issue
  • - Volume 2017
  • - Article ID 4901017
  • - Research Article

R Peak Detection Method Using Wavelet Transform and Modified Shannon Energy Envelope

Jeong-Seon Park | Sang-Woong Lee | Unsang Park
  • Special Issue
  • - Volume 2017
  • - Article ID 5907264
  • - Research Article

Hybrid Disease Diagnosis Using Multiobjective Optimization with Evolutionary Parameter Optimization

MadhuSudana Rao Nalluri | Kannan K. | ... | Diptendu Sinha Roy
  • Special Issue
  • - Volume 2017
  • - Article ID 5485080
  • - Research Article

Diagnosis of Alzheimer’s Disease Based on Structural MRI Images Using a Regularized Extreme Learning Machine and PCA Features

Ramesh Kumar Lama | Jeonghwan Gwak | ... | Sang-Woong Lee
  • Special Issue
  • - Volume 2017
  • - Article ID 4080874
  • - Research Article

Cell Detection Using Extremal Regions in a Semisupervised Learning Framework

Nisha Ramesh | Ting Liu | Tolga Tasdizen
  • Special Issue
  • - Volume 2017
  • - Article ID 9283480
  • - Research Article

Low-Grade Glioma Segmentation Based on CNN with Fully Connected CRF

Zeju Li | Yuanyuan Wang | ... | Ying Mao
  • Special Issue
  • - Volume 2017
  • - Article ID 7406896
  • - Research Article

A Real-Time Analysis Method for Pulse Rate Variability Based on Improved Basic Scale Entropy

Yongxin Chou | Ruilei Zhang | ... | Benlian Xu
  • Special Issue
  • - Volume 2017
  • - Article ID 4108720
  • - Research Article

Patient-Specific Deep Architectural Model for ECG Classification

Kan Luo | Jianqing Li | ... | Alfred Cuschieri
Journal of Healthcare Engineering
 Journal metrics
Acceptance rate37%
Submission to final decision99 days
Acceptance to publication48 days
CiteScore2.600
Impact Factor1.803
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