Structured Graded Lung Rehabilitation for Children with Mechanical Ventilation

Ren, Lei; Hu, Jing; Li, Mei; Zhang, Ling; Xia, Jinyue

doi:10.32604/csse.2022.018640

Cited by 5 publications

(2 citation statements)

References 31 publications

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“…At the same time, CCA anonymous dynamic group signature mechanism is introduced, which greatly improves the time efficiency of generating proof. The signature mechanism is more secure and efficient in computing and communication cost under the data security management framework of medical network community [24], based on CB and FL. At the same time, the NIZK scheme is used to realize the security sharing of medical data, and verify the correctness of medical data under the sharing operation on the smart contract.…”

Section: Data Privacy Protection Mechanism Based On Federated Learnin...mentioning

confidence: 99%

Privacy Data Management Mechanism Based on Blockchain and Federated Learning

Mo¹,

Ji²,

Wang³

et al. 2023

Computers, Materials &Amp; Continua

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Due to the extensive use of various intelligent terminals and the popularity of network social tools, a large amount of data in the field of medical emerged. How to manage these massive data safely and reliably has become an important challenge for the medical network community. This paper proposes a data management framework of medical network community based on Consortium Blockchain (CB) and Federated learning (FL), which realizes the data security sharing between medical institutions and research institutions. Under this framework, the data security sharing mechanism of medical network community based on smart contract and the data privacy protection mechanism based on FL and alliance chain are designed to ensure the security of data and the privacy of important data in medical network community, respectively. An intelligent contract system based on Keyed-Homomorphic Public Key (KH-PKE) Encryption scheme is designed, so that medical data can be saved in the CB in the form of ciphertext, and the automatic sharing of data is realized. Zero knowledge mechanism is used to ensure the correctness of shared data. Moreover, the zero-knowledge mechanism introduces the dynamic group signature mechanism of chosen ciphertext attack (CCA) anonymity, which makes the scheme more efficient in computing and communication cost. In the end of this paper, the performance of the scheme is analyzed from both asymptotic and practical aspects. Through experimental comparative analysis, the scheme proposed in this paper is more effective and feasible.

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Section: Data Privacy Protection Mechanism Based On Federated Learnin...mentioning

confidence: 99%

Privacy Data Management Mechanism Based on Blockchain and Federated Learning

Mo¹,

Ji²,

Wang³

et al. 2023

Computers, Materials &Amp; Continua

View full text Add to dashboard Cite

show abstract

“…Compared with deep neural network, DF model is simple, highly interpretable, low computational overhead, adaptive and scalable in complexity, and has strong robustness and fewer hyperparameters to a certain extent. Therefore, DF has attracted extensive attention from research field and has been applied in many scenarios, such as financial analysis [18][19][20][21], medical diagnosis [22][23][24][25], remote sensing [26][27][28], software defect prediction [29][30][31][32] and so on. However, in DF the average value of all decision tree results is taken as the result of the corresponding forest, which ignores the accuracy difference of each decision tree.…”

Section: Introductionmentioning

confidence: 99%

WDBM: Weighted Deep Forest Model Based Bearing Fault Diagnosis Method

Gao¹,

Wang²,

Wang³

et al. 2022

Computers, Materials &Amp; Continua

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In the research field of bearing fault diagnosis, classical deep learning models have the problems of too many parameters and high computing cost. In addition, the classical deep learning models are not effective in the scenario of small data. In recent years, deep forest is proposed, which has less hyper parameters and adaptive depth of deep model. In addition, weighted deep forest (WDF) is proposed to further improve deep forest by assigning weights for decisions trees based on the accuracy of each decision tree. In this paper, weighted deep forest model-based bearing fault diagnosis method (WDBM) is proposed. The WDBM is regard as a novel bearing fault diagnosis method, which not only inherits the WDF's advantages-strong robustness, good generalization, less parameters, faster convergence speed and so on, but also realizes effective diagnosis with high precision and low cost under the condition of small samples. To verify the performance of the WDBM, experiments are carried out on Case Western Reserve University bearing data set (CWRU). Experiments results demonstrate that WDBM can achieve comparative recognition accuracy, with less computational overhead and faster convergence speed.

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Research progress in pulmonary rehabilitation in patients who have been weaned off mechanical ventilation: A review article

Xu,

Si,

Feng

et al. 2024

THC

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BACKGROUND: Patients who have been treated with mechanical ventilation for more than 72 hours are susceptible to symptoms such as hypoxia and respiratory muscle fatigue after weaning, which may result in weaning difficulty and delay, as well as an increased incidence of negative emotions such as anxiety and depression. Correct pulmonary rehabilitation exercise technique and timing can improve the weaning success rate, reduce the disability rate, and reduce the incidence of pulmonary infection, as well as reduce medical expenses. OBJECTIVE: This article provides a review of pulmonary rehabilitation interventions for mechanically ventilated patients, searching relevant literature through databases such as CNKI and PubMed, aiming to provide guidance for the successful weaning of mechanically ventilated patients. METHODS: We selected articles related to pulmonary rehabilitation interventions for mechanically ventilated patients from CNKI (China National Knowledge Infrastructure) and PubMed over the years. RESULTS: This article provides a comprehensive review of the research on lung rehabilitation for patients who are mechanically ventilated during the weaning process in an effort to serve as a guide for a successful transition from mechanical ventilation. CONCLUSION: Early pulmonary rehabilitation training can effectively increase the pulmonary function level and ventilation function of patients and reduce the duration of mechanical ventilation and hospitalization, and is an effective, safe, and feasible treatment method.

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Structured Graded Lung Rehabilitation for Children with Mechanical Ventilation

Cited by 5 publications

References 31 publications

Privacy Data Management Mechanism Based on Blockchain and Federated Learning

Privacy Data Management Mechanism Based on Blockchain and Federated Learning

WDBM: Weighted Deep Forest Model Based Bearing Fault Diagnosis Method

Research progress in pulmonary rehabilitation in patients who have been weaned off mechanical ventilation: A review article

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