Table of Content

Computer Modeling of Artificial Intelligence and Medical Imaging

Submission Deadline: 15 March 2023 Submit to Special Issue

Guest Editors

Prof. Yu-Dong Zhang, University of Leicester, UK
Prof. Juan Manuel Gorriz, University of Granada, Spain
Prof. Zhengchao Dong, Columbia University and New York State Psychiatric Institute, USA
Prof. Qilong Wang, Nanjing Medical University, China
Prof. Shu-Wen Chen, Jiangsu Second Normal University, China

Summary

Over the recent years, we have saw the artificial intelligence (AI) methods reforming the zone of medical imaging. Many AI-based models have been created and improved to related medical image analysis and interpretation. Particularly, deep learning (DL) methods have exhibited brilliant performances in the screening and diagnosing numerous disorders and diseases. A challenge of AI-driven products is to develop more accurate diagnosis systems through DL models by taking benefits of learning patterns and relationships directly from medical imaging data,.


This Special Section aims to invite original research papers that report the latest advances of medical imaging-oriented AI models. Submissions should clarify the substantive improvements on work that has already been published, accepted for publication, or submitted in parallel to other conferences or journals.

 

The topics of interest include, but are not limited to following

Ø Advanced AI and DL models

Ø Supervised or semi-supervised learning

Ø Diagnosis using biomarkers and imaging-based methods

Ø Transfer learning methods for diagnosis and segmentation

Ø Genotype, phenotype, and pathogenesis

Ø Explainable/Trustworthy AI-based prediction, segmentation, and diagnosis

Ø Medical and healthcare equipment/resources supply chain management

Ø Wearable sensors or IoT based public health support, patient behavior and emotion monitoring

Ø VR/AR computer-aided diagnosis system

Ø 2D and 3D visualization

Ø Design and development of vaccine & targeted drug

Ø Epidemic dynamics prediction and forecast

Ø Graph neural network

Ø Computational prediction of protein structure associated with virus

Ø Socio-economic impacts of infectious disease interventions

Ø Survival and risk of recurrence estimation

Ø Recovery prediction in rehabilitation

Ø Potential therapeutics

Ø Public health system or strategies

Ø Medical image registration

Ø Radiomics



Published Papers


  • Open Access

    REVIEW

    A Survey of Convolutional Neural Network in Breast Cancer

    Ziquan Zhu, Shui-Hua Wang, Yu-Dong Zhang
    CMES-Computer Modeling in Engineering & Sciences
    (This article belongs to this Special Issue: Computer Modeling of Artificial Intelligence and Medical Imaging)
    Abstract Problems: For people all over the world, cancer is one of the most feared diseases. Cancer is one of the major obstacles to improving life expectancy in countries around the world and one of the biggest causes of death before the age of 70 in 112 countries. Among all kinds of cancers, breast cancer is the most common cancer for women. The data showed that female breast cancer had become one of the most common cancers. Aims: A large number of clinical trials have proved that if breast cancer is diagnosed at an early stage, it could give patients more… More >

  • Open Access

    REVIEW

    A Review of Device-Free Indoor Positioning for Home-Based Care of the Aged: Techniques and Technologies

    Geng Chen, Lili Cheng, Rui Shao, Qingbin Wang, Shuihua Wang
    CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.3, pp. 1901-1940, 2023, DOI:10.32604/cmes.2023.024901
    (This article belongs to this Special Issue: Computer Modeling of Artificial Intelligence and Medical Imaging)
    Abstract With the development of urbanization, the problem of neurological diseases brought about by population aging has gradually become a social problem of worldwide concern. Aging leads to gradual degeneration of the central nervous system, shrinkage of brain tissue, and decline in physical function in many elderlies, making them susceptible to neurological diseases such as Alzheimer’s disease (AD), stroke, Parkinson’s and major depressive disorder (MDD). Due to the influence of these neurological diseases, the elderly have troubles such as memory loss, inability to move, falling, and getting lost, which seriously affect their quality of life. Tracking and positioning of elderly with… More >

    Graphic Abstract

    A Review of Device-Free Indoor Positioning for Home-Based Care of the Aged: Techniques and Technologies

  • Open Access

    ARTICLE

    Brain Functional Networks with Dynamic Hypergraph Manifold Regularization for Classification of End-Stage Renal Disease Associated with Mild Cognitive Impairment

    Zhengtao Xi, Chaofan Song, Jiahui Zheng, Haifeng Shi, Zhuqing Jiao
    CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.3, pp. 2243-2266, 2023, DOI:10.32604/cmes.2023.023544
    (This article belongs to this Special Issue: Computer Modeling of Artificial Intelligence and Medical Imaging)
    Abstract The structure and function of brain networks have been altered in patients with end-stage renal disease (ESRD). Manifold regularization (MR) only considers the pairing relationship between two brain regions and cannot represent functional interactions or higher-order relationships between multiple brain regions. To solve this issue, we developed a method to construct a dynamic brain functional network (DBFN) based on dynamic hypergraph MR (DHMR) and applied it to the classification of ESRD associated with mild cognitive impairment (ESRDaMCI). The construction of DBFN with Pearson’s correlation (PC) was transformed into an optimization model. Node convolution and hyperedge convolution superposition were adopted to… More >

    Graphic Abstract

    Brain Functional Networks with Dynamic Hypergraph Manifold Regularization for Classification of End-Stage Renal Disease Associated with Mild Cognitive Impairment

  • Open Access

    ARTICLE

    A Study of BERT-Based Classification Performance of Text-Based Health Counseling Data

    Yeol Woo Sung, Dae Seung Park, Cheong Ghil Kim
    CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.1, pp. 795-808, 2023, DOI:10.32604/cmes.2022.022465
    (This article belongs to this Special Issue: Computer Modeling of Artificial Intelligence and Medical Imaging)
    Abstract The entry into a hyper-connected society increases the generalization of communication using SNS. Therefore, research to analyze big data accumulated in SNS and extract meaningful information is being conducted in various fields. In particular, with the recent development of Deep Learning, the performance is rapidly improving by applying it to the field of Natural Language Processing, which is a language understanding technology to obtain accurate contextual information. In this paper, when a chatbot system is applied to the healthcare domain for counseling about diseases, the performance of NLP integrated with machine learning for the accurate classification of medical subjects from… More >

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