J Med Syst
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The aim of this study was to investigate the alterations in regional homogeneity assessed by fMRI in patients with migraine without aura (MWoA). Fifty-six eligible MWoA patients and 32 matched healthy volunteers were enrolled in this study. MWoA patients were divided into three groups according to the headache days per month within 3 months: infrequent episodic migraine (IEM) group, frequent episodic migraine (FEM) group, and chronic migraine (CM) group. ⋯ In the IEM group, the changes of function focus on the regions associated with coding, conduction and regulation of pain signals. In the FEM group, functional alterations mainly concentrated on the regions associated with pain regulation and emotion cognition. In the CM group, the changes focus on the regions related to spatial attention and cognition, affective disorders and pain feedback, which may be associated with migraine production, development and chronification.
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Remotely monitoring a patient's condition is a serious issue and must be addressed. Remote health monitoring systems (RHMS) in telemedicine refers to resources, strategies, methods and installations that enable doctors or other medical professionals to work remotely to consult, diagnose and treat patients. The goal of RHMS is to provide timely medical services at remote areas through telecommunication technologies. ⋯ This study introduces a comprehensive and inclusive review on the prioritisation of patients with MCDs in telemedicine applications. Furthermore, it presents the challenges and open issues regarding patient prioritisation in telemedicine. The findings of this study are as follows: (1) The limitations and problems of existing patients' prioritisation with MCDs are presented and emphasised. (2) Based on the analysis of the academic literature, an accurate solution for remote prioritisation in a large scale of patients with MCDs was not presented. (3) There is an essential need to produce a new multiple-criteria decision-making theory to address the current problems in the prioritisation of patients with MCDs.
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Hospital scheduling presents huge challenges for the healthcare industry. Various studies have been conducted in many different countries with focus on both elective and non-elective surgeries. There are important variables and factors that need to be taken into considerations. ⋯ Nonetheless, its feasibility is further tested as the problems size and the computation times is getting bigger and longer. Application of heuristic methods is the way forward to ensure better practicality of the proposed model. In the end, the potential benefit of this study and the proposed model is discussed.
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Wearable devices, wireless networks and body area networks have become an effective way to solve the problem of human health monitoring and care. However, the radiation problems of wireless devices, the power supply problems of wearable devices and the deployment of body area networks have become obstacles to their wide application in the field of health care. In order to solve the above problems, this paper studies and designs a wearable health medical body area network which is convenient for human health monitoring and medical care, starting from low-cost deployment of wireless wearable devices and active control of wireless radiation. ⋯ Then, in order to minimize the charging cost and maximize the global charging utility of single source and multiple points in a finite time slot, an approximate algorithm for the optimal charging sequence based on 01 knapsack problem, i.e., the access path of wireless wearable devices, is designed. Then, an active radiation control algorithm for wearable medical health body area network is proposed, which can actively control the transmission power and radiation status of these wireless devices. Finally, simulation results show that the proposed algorithm is better than battery-powered wireless body area network and wireless rechargeable body area network, 16% and 44% reduction of devices, 25%13% reduction of energy consumption, 26% reduction of radiation, and 5.18 and 1.13 times improvement of signal quality.
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Virtual and Augmented Reality has experienced a steady growth in medicine in recent years. At the same time, the radiological images play a central role in the diagnosis and planification of surgical approaches. ⋯ This application allows to move beyond traditional two-dimensional images towards three-dimensional models that can be visualized and manipulated with both Augmented Reality and Virtual Reality. We propose possible approaches to automate the segmentation of radiological images, using computer vision techniques and Artificial Intelligence.