Cerebral Micro-Bleeding Detection Based on Densely Connected Neural Network

Wang, Shuihua; Tang, Chaosheng; Sun, Jian‐Ping; Zhang, Yudong

doi:10.3389/fnins.2019.00422

Cited by 70 publications

(52 citation statements)

References 45 publications

(44 reference statements)

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“…The gradual popularity of big data technology has enabled a number of successful big IoH applications [25][26][27]. However, in our suggested IoH data fusion and mining method PDFM, there are several limitations.…”

Section: Further Discussionmentioning

confidence: 94%

Multi-Source Medical Data Integration and Mining for Healthcare Services

et al. 2020

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With the advent of Internet of Health (IoH) age, traditional medical or healthy services are gradually migrating to the Web or Internet and have been producing a considerable amount of medical data associated with patients, doctors, medicine, medical infrastructure and so on. Effective fusion and analyses of these IoH data are of positive significances for the scientific disaster diagnosis and medical care services. However, IoH data are often distributed across different departments and contain partial user privacy. Therefore, it is often a challenging task to effectively integrate or mine the sensitive IoH data, during which user privacy is not disclosed. To overcome the above difficulty, we put forward a novel multi-source medical data integration and mining solution for better healthcare services, named PDFM (Privacy-free Data Fusion and Mining). Through PDFM, we can search for similar medical records in a time-efficient and privacy-preserving manner, so as to offer patients with better medical and health services. A group of experiments are enacted and implemented to demonstrate the feasibility of the proposal in this work.

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Section: Further Discussionmentioning

confidence: 94%

Multi-Source Medical Data Integration and Mining for Healthcare Services

et al. 2020

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“…Use the Lagrange multiplier method to derive the parameter j w in Eq. (11), and set its derivative to 0. The expression for the parameter j w is as follows:…”

Section: B Takagi-sugeno-kang Fuzzy Systemmentioning

confidence: 99%

“…The study of emotions through physiological signals has become increasingly mature. Various intelligent recognition algorithms are used in various fields [4][5][6][7][8][9][10][11][12], among which methods for emotion recognition are introduced as follows. The MIT laboratory led by Picard performed a series of emotional recognition experiments with multiple physiological parameters through signal preprocessing and pattern recognition algorithms.…”

Section: Introductionmentioning

confidence: 99%

Anxiety Recognition of College Students Using a Takagi-Sugeno-Kang Fuzzy System Modeling Method and Deep Features

Meng

Zhang

2020

IEEE Access

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College students are the most active, most sensitive, and most prone group with respect to various psychological problems in contemporary society. In recent years, with the intensification of social competition, including various pressures such as studies, examinations, economic loss, emotional loss, and employment, the incidence of anxiety, depression and suicide rates has increased. To effectively pay attention to the psychological development of college students and to strengthen mental health education, this research proposes a method to automatically identify the anxiety of college students using a Takagi-Sugeno-Kang (TSK) fuzzy system and deep features. First, preprocess the collected EEG of college students. Secondly, use convolutional neural network (CNN) to extract deep features from the input data. Finally, TSK fuzzy system is used to classify features to obtain the final recognition result. Through experiments on standard data sets and self-made data sets, the experimental results verify the superiority of the anxiety identification method used in this study. The experimental results further demonstrate that the depth features have richer information than traditional features. The noise immunity of TSK fuzzy system makes it show good classification performance and generalization. The recognition results can quickly locate students with anxiety disorders and narrow the scope of investigation for students with psychological problems. The automatic recognition of college students' anxiety can improve the efficiency of schools and teachers in investigating students' psychological problems. This research has very good practical application value.

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“…The Halcyon system is the first medical linear accelerator to realize 100% image guidance in the world [4]. It offers the advantages of high integration, high automation and high intelligence [5]. It further promotes radiotherapy from conventional "precise radiotherapy" to "intelligent precise radiotherapy" [6].…”

Section: Research Backgroundmentioning

confidence: 99%

Intelligent IoT-based large-scale inverse planning system considering postmodulation factors

Lan

Yue

et al. 2020

Complex Intell. Syst.

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The model and algorithm of intensity-modulated radiotherapy (IMRT) are updated increasingly quickly, but the hardware upgrade of primary hospitals often lags behind. The new generation of intelligent precise radiotherapy platforms provides users with intelligent medical consortium services using big data, artificial intelligence and industrial Internet of Things technology. This technology can ensure that under the real-time guidance of a professional medical consortium, primary hospitals can realize rapid large-scale reverse planning design and can more accurately consider many factors of postprocessing. Although large-scale healthcare systems, such as volumetric-modulated arc therapy and other accurate radiotherapy technologies, have developed rapidly, the development of step-and-shoot-mode IMRT technology is still very important for developing countries. For software, in addition to the conformity of the dose distribution, the modulation speed, convenience and stability of the later dose delivery should also be considered in inverse planning. Therefore, this paper analyzes the main problems in conventional IMRT inverse planning, including the smoothing of the fluence map, the selection of the gantry angle and the dose leakage of tongue–groove effects. To address these issues, a novel Intelligent IoT-based large-scale inverse planning strategy with the key factors of the postmodulation is developed, and a detailed flow chart is also provided. The scheme consists of two steps. The first step is to obtain a relatively optimal combination of gantry angles by considering the dose distribution requirements and constraints and the modulation requirements and constraints. The second step is to optimize the intensity map, to smooth the map based on prior knowledge according to the determined angles, and to obtain the final modulation scheme according to the relevant objectives and constraints of the map decomposition (leaf sequencing). In an experiment, we calculate and validate the clinical head and neck case. Because of the special gantry angle selection, the angle combination is optimized from the initial equivalent distribution to adapt to the target area and protect the nontarget area. The value of the objective function varies greatly after the optimization, especially in the target area, and the target value decreases by approximately 10%. On this basis, we smooth the fluence map by a partial differential equation with prior knowledge and a minimization of the total number of monitor units. It is also shown from the objective function value that the target value is essentially unchanged for the target area, while for the nontarget area, the value decreases by 16%, which is very impressive.

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Cerebral Micro-Bleeding Detection Based on Densely Connected Neural Network

Cited by 70 publications

References 45 publications

Multi-Source Medical Data Integration and Mining for Healthcare Services

Multi-Source Medical Data Integration and Mining for Healthcare Services

Anxiety Recognition of College Students Using a Takagi-Sugeno-Kang Fuzzy System Modeling Method and Deep Features

Intelligent IoT-based large-scale inverse planning system considering postmodulation factors

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