About the Journal
Innovation and rapid technological development in intelligent medicine and healthcare impacts profoundly on many aspects of people’s life. It is believed that developing advanced intelligent algorithms and systems has the potential to save medical resources, reduce administrative costs and burdens, improve integration between medical worker and care providers, reduce medical errors, and improve medical and healthcare quality and patient outcomes. Along with the world’s population growing and aging, challenges in medicine and healthcare on a global scale are very apparent. The vision of Journal of Intelligent Medicine and Healthcare is to attack these apparent challenges through the design of algorithms, mathematical methods, systems, devices, and policies for medicine and healthcare in an intelligent way.
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Open Access
ARTICLE
Multiple Sclerosis Predictions and Sensitivity Analysis Using Robust Models
Journal of Intelligent Medicine and Healthcare, Vol.3, pp. 1-14, 2025, DOI:10.32604/jimh.2022.062824 - 04 April 2025
Abstract Multiple Sclerosis (MS) is a disease that disrupts the flow of information within the brain. It affects approximately 1 million people in the US. And remains incurable. MS treatments can cause side effects and impact the quality of life and even survival rates. Based on existing research studies, we investigate the risks and benefits of three treatment options based on methylprednisolone (a corticosteroid hormone medication) prescribed in (1) high-dose, (2) low-dose, or (3) no treatment. The study currently prescribes one treatment to all patients as it has been proven to be the most effective on More >
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Open Access
ARTICLE
A Work Review on Clinical Laboratory Data Utilizing Machine Learning Use-Case Methodology
Journal of Intelligent Medicine and Healthcare, Vol.2, pp. 1-14, 2024, DOI:10.32604/jimh.2023.046995
Abstract More than 140 autoimmune diseases have distinct autoantibodies and symptoms, and it makes it challenging to construct an appropriate model using Machine Learning (ML) for autoimmune disease. Arthritis-related autoimmunity requires special attention. Although many conventional biomarkers for arthritis have been established, more biomarkers of arthritis autoimmune diseases remain to be identified. This review focuses on the research conducted using data obtained from clinical laboratory testing of real-time arthritis patients. The collected data is labelled the Arthritis Profile Data (APD) dataset. The APD dataset is the retrospective data with many missing values. We undertook a comprehensive… More >
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Open Access
ARTICLE
Securing Mobile Cloud-Based Electronic Health Records: A Blockchain-Powered Cryptographic Solution with Enhanced Privacy and Efficiency
Journal of Intelligent Medicine and Healthcare, Vol.2, pp. 15-34, 2024, DOI:10.32604/jimh.2024.048784
Abstract The convergence of handheld devices and cloud-based computing has transformed how Electronic Health Records (EHRs) are stored in mobile cloud paradigms, offering benefits such as affordability, adaptability, and portability. However, it also introduces challenges regarding network security and data confidentiality, as it aims to exchange EHRs among mobile users while maintaining high levels of security. This study proposes an innovative blockchain-based solution to these issues and presents secure cloud storage for healthcare data. To provide enhanced cryptography, the proposed method combines an enhanced Blowfish encryption method with a new key generation technique called Elephant Herding… More >
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Open Access
ARTICLE
Enhancing Multi-Modality Medical Imaging: A Novel Approach with Laplacian Filter + Discrete Fourier Transform Pre-Processing and Stationary Wavelet Transform Fusion
Journal of Intelligent Medicine and Healthcare, Vol.2, pp. 35-53, 2024, DOI:10.32604/jimh.2024.051340
Abstract Multi-modality medical images are essential in healthcare as they provide valuable insights for disease diagnosis and treatment. To harness the complementary data provided by various modalities, these images are amalgamated to create a single, more informative image. This fusion process enhances the overall quality and comprehensiveness of the medical imagery, aiding healthcare professionals in making accurate diagnoses and informed treatment decisions. In this study, we propose a new hybrid pre-processing approach, Laplacian Filter + Discrete Fourier Transform (LF+DFT), to enhance medical images before fusion. The LF+DFT approach highlights key details, captures small information, and sharpens… More >
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Open Access
ARTICLE
Multiple Sclerosis Predictions and Sensitivity Analysis Using Robust Models
Journal of Intelligent Medicine and Healthcare, Vol.3, pp. 1-14, 2025, DOI:10.32604/jimh.2022.062824
Abstract Multiple Sclerosis (MS) is a disease that disrupts the flow of information within the brain. It affects approximately 1 million people in the US. And remains incurable. MS treatments can cause side effects and impact the quality of life and even survival rates. Based on existing research studies, we investigate the risks and benefits of three treatment options based on methylprednisolone (a corticosteroid hormone medication) prescribed in (1) high-dose, (2) low-dose, or (3) no treatment. The study currently prescribes one treatment to all patients as it has been proven to be the most effective on More >
Copyright © 2025 The Author(s). Published by Tech Science Press.
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