Mian Muhammad Danyal^1,2, Sarwar Shah Khan^3,4,*, Rahim Shah Khan⁵, Saifullah Jan², Naeem ur Rahman⁶

Journal of Intelligent Medicine and Healthcare, Vol.2, pp. 35-53, 2024, DOI:10.32604/jimh.2024.051340 - 08 July 2024

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 >

Umer Nauman¹, Yuhong Zhang², Zhihui Li³, Tong Zhen^1,3,*

Journal of Intelligent Medicine and Healthcare, Vol.2, pp. 15-34, 2024, DOI:10.32604/jimh.2024.048784 - 11 April 2024

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 >

Uma Ramasamy^*, Sundar Santhoshkumar

Journal of Intelligent Medicine and Healthcare, Vol.2, pp. 1-14, 2024, DOI:10.32604/jimh.2023.046995 - 10 January 2024

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 >

Colleen Crangle^1,2,*, Bude Piccin², Lara Hyde³, Elin Östman⁴

Journal of Intelligent Medicine and Healthcare, Vol.1, No.2, pp. 91-102, 2022, DOI:10.32604/jimh.2022.038379 - 05 January 2023

Abstract Postprandial glucose responses provide vital information on an individual’s risk of major diet-related chronic diseases. This study features digital health technology, namely Continuous Glucose Monitoring (CGM) sensors, along with mobile devices (iPhones running an app) used to collect data from individuals and their environment, specifically nutritional information on what they eat and drink. The paper presents a retrospective analysis of data collected during an investigation into the use of a functional drink taken as a supplement with a standardized meal to reduce postprandial responses to that meal. Given that there are consequential differences between individuals… More >

Zhiqiang He^*

Journal of Intelligent Medicine and Healthcare, Vol.1, No.2, pp. 79-89, 2022, DOI:10.32604/jimh.2022.036624 - 05 January 2023

Abstract Electrocardiogram (ECG) is widely used to detect arrhythmia. Atrial fibrillation, atrioventricular block, premature beats, etc. can all be diagnosed by ECG. When the distribution of training data and test data is inconsistent, the accuracy of the model will be affected. This phenomenon is called dataset shift. In the real-world heartbeat classification system, the heartbeat of the training set and test set often comes from patients of different ages and genders, so there are differences in the distribution of data sets. The main challenge in applying machine learning algorithms to clinical AI systems is dataset shift.… More >

Liyuan Chen^1,2,3,*, Zhenhua Luo^1,2,3, Xianhua Li^1,2,3, Ya Chen^1,2,3, Mengyu Chang⁴

Journal of Intelligent Medicine and Healthcare, Vol.1, No.2, pp. 69-77, 2022, DOI:10.32604/jimh.2022.036288 - 05 January 2023

Abstract Objective: Explore the homogeneous management of appropriate technology for Traditional Chinese Medicine (TCM) care based on the county medical community platform. Methods: The hospital has formed a county medical community since 2020, based on which the platform develops homogeneous management of appropriate technologies for TCM nursing, establishes a medical training center, a remote consultation center and a TCM nursing quality control center, strengthens the construction of TCM nursing specialties, integrates TCM with public health and consolidates information support. The “321” model was developed, with January 2021 to December 2021 as the post-implementation period and January More >

Shangwe Charmant Nicolas^*

Journal of Intelligent Medicine and Healthcare, Vol.1, No.2, pp. 55-68, 2022, DOI:10.32604/jimh.2022.033058 - 05 January 2023

Abstract The COVID-19 outbreak has taken a toll on humankind and the world’s health to a breaking point, causing millions of deaths and cases worldwide. Several preventive measures were put in place to counter the escalation of COVID-19. Usage of face masks has proved effective in mitigating various airborne diseases, hence immensely advocated by the WHO (World Health Organization). A compound CNN-LSTM network is developed and employed for the recognition of masked and none masked personnel in this paper. 3833 RGB images, including 1915 masked and 1918 unmasked images sampled from the Real-World Masked Face Dataset More >

Yicheng Xie^1,*, Jinyue Xia²

Journal of Intelligent Medicine and Healthcare, Vol.1, No.1, pp. 43-54, 2022, DOI:10.32604/jimh.2022.032405 - 14 June 2022

Abstract Lung cancer is now the most common type of cancer worldwide, with high levels of morbidity and mortality. The cost of treatment and emotional stress put a high burden on families and society. This paper aims to collect relevant information and provide predictive analysis for the prognosis of patients with lung cancer. Using the public data of SEER database and the method of machine learning, a model is constructed to predict the five-year survival of patients with lung cancer. The re-coding method is used for data processing, the eigenvalues are re-coded to adapt to the… More >

Lei Ren^1,*, Hao Hua²

Journal of Intelligent Medicine and Healthcare, Vol.1, No.1, pp. 33-42, 2022, DOI:10.32604/jimh.2022.032093 - 14 June 2022

Abstract The theoretical framework, terminology and coding of the International Classification of Functioning, Disability and Health for Children and Youth are useful tools for content analysis of physical activity guidelines for children and adolescents. The guidelines for physical activity for children and adolescents at home and abroad have their own policy background and health-related theoretical basis for healthy development. The formulation and implementation of physical activity guidelines for children and adolescents should be based on the national health policy, propose programs suitable for children and adolescents, and guide the implementation of the guidelines. This paper summarizes More >

Nisha Mary¹, Bilal Khan^1,*, Abdullah A Asiri², Fazal Muhammad³, Samar Alqhtani⁴, Khlood M Mehdar⁵, Hanan Talal Halwani⁴, Turki Aleyani⁴, Khalaf A Alshamrani²

Journal of Intelligent Medicine and Healthcare, Vol.1, No.1, pp. 11-31, 2022, DOI:10.32604/jimh.2022.030161 - 14 June 2022

Abstract Prognosis of HD is a complex task that requires experience and expertise to predict in the early stage. Nowadays, heart failure is rising due to the inherent lifestyle. The healthcare industry generates dense records of patients, which cannot be managed manually. Such an amount of data is very significant in the field of data mining and machine learning when gathering valuable knowledge. During the last few decades, researchers have used different approaches for the prediction of HD, but still, the major problem is the uncertainty factor in the output data and also there is a… More >