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Open Access
Article
Publication date: 12 June 2017

Lichao Zhu, Hangzhou Yang and Zhijun Yan

The purpose of this paper is to develop a new method to extract medical temporal information from online health communities.

Abstract

Purpose

The purpose of this paper is to develop a new method to extract medical temporal information from online health communities.

Design/methodology/approach

The authors trained a conditional random-filed model for the extraction of temporal expressions. The temporal relation identification is considered as a classification task and several support vector machine classifiers are built in the proposed method. For the model training, the authors extracted some high-level semantic features including co-reference relationship of medical concepts and the semantic similarity among words.

Findings

For the extraction of TIMEX, the authors find that well-formatted expressions are easy to recognize, and the main challenge is the relative TIMEX such as “three days after onset”. It also shows the same difficulty for normalization of absolute date or well-formatted duration, whereas frequency is easier to be normalized. For the identification of DocTimeRel, the result is fairly well, and the relation is difficult to identify when it involves a relative TIMEX or a hypothetical concept.

Originality/value

The authors proposed a new method to extract temporal information from the online clinical data and evaluated the usefulness of different level of syntactic features in this task.

Details

International Journal of Crowd Science, vol. 1 no. 2
Type: Research Article
ISSN: 2398-7294

Keywords

Open Access
Article
Publication date: 16 April 2019

Kuang Junwei, Hangzhou Yang, Liu Junjiang and Yan Zhijun

Previous dynamic prediction models rarely handle multi-period data with different intervals, and the large-scale patient hospital records are not effectively used to improve the…

3311

Abstract

Purpose

Previous dynamic prediction models rarely handle multi-period data with different intervals, and the large-scale patient hospital records are not effectively used to improve the prediction performance. This paper aims to focus on the prediction of cardiovascular disease using the improved long short-term memory (LSTM) model.

Design/methodology/approach

A new model based on the traditional LSTM was proposed to predict cardiovascular disease. The irregular time interval is smoothed to obtain the time parameter vector, and it is used as the input of the forgetting gate of LSTM to overcome the prediction obstacle caused by the irregular time interval.

Findings

The experimental results show that the dynamic prediction model proposed in this paper obtained a significant better classification performance compared with the traditional LSTM model.

Originality/value

In this paper, the authors improved the LSTM by smoothing the irregular time between different medical stages of the patient to obtain the temporal feature vector.

Details

International Journal of Crowd Science, vol. 3 no. 1
Type: Research Article
ISSN: 2398-7294

Keywords

Article
Publication date: 30 November 2021

Hangzhou Yang and Huiying Gao

Recommending suitable content for users of online health communities (OHCs) is critical for overcoming information overload problem and facilitate medical decision making, but…

Abstract

Purpose

Recommending suitable content for users of online health communities (OHCs) is critical for overcoming information overload problem and facilitate medical decision making, but remains not fully investigated. This study aims to provide a content recommendation approach to automatically match valuable health-related information for OHC members.

Design/methodology/approach

A framework of health-related content recommendation was proposed by leveraging rich social information in online communities. The authors constructed user influence relationship (UIR) utilizing users' interaction records, user profiles and user-generated content. The initial user rating matrix and the user post matching matrix were then created by analyzing text content of posts. Finally, the user rating matrix and the recommended content were generated for community members. Datasets were collected from an OHC to evaluate the effectiveness of the proposed approach.

Findings

The experimental results revealed that the proposed method statistically outperformed baseline models in content recommendation for users of OHCs.

Research limitations/implications

The incorporation of social information can significantly enhance the performance of content recommendation in OHCs. The user post matching degree based on text analysis can improve the effectiveness of recommendation.

Practical implications

This study potentially contributes to the social support exchange and medical decision making of community members and the sustainable prosperity of OHCs.

Originality/value

This study proposes a novel social content recommendation method for online health consumers based on UIRs by leveraging social information in OHCs. The results indicate the significance of social information in content recommendation of healthcare social media.

Details

Industrial Management & Data Systems, vol. 122 no. 2
Type: Research Article
ISSN: 0263-5577

Keywords

Article
Publication date: 25 August 2021

Hangzhou Yang and Huiying Gao

Online health communities (OHCs) are platforms that help health consumers to communicate with each other and obtain social support for better healthcare outcomes. However, it is…

Abstract

Purpose

Online health communities (OHCs) are platforms that help health consumers to communicate with each other and obtain social support for better healthcare outcomes. However, it is usually difficult for community members to efficiently find appropriate peers for social support exchange due to the tremendous volume of users and their generated content. Most of the existing user recommendation systems fail to effectively utilize the rich social information in social media, which can lead to unsatisfactory recommendation performance. The purpose of this study is to propose a novel user recommendation method for OHCs to fill this research gap.

Design/methodology/approach

This study proposed a user recommendation method that utilized the adapted matrix factorization (MF) model. The implicit user behavior networks and the user influence relationship (UIR) network were constructed using the various social information found in OHCs, including user-generated content (UGC), user profiles and user interaction records. An experiment was conducted to evaluate the effectiveness of the proposed approach based on a dataset collected from a famous online health community.

Findings

The experimental results demonstrated that the proposed method outperformed all baseline models in user recommendation using the collected dataset. The incorporation of social information from OHCs can significantly improve the performance of the proposed recommender system.

Practical implications

This study can help users build valuable social connections efficiently, enhance communication among community members, and potentially contribute to the sustainable prosperity of OHCs.

Originality/value

This study introduces the construction of the UIR network in OHCs by integrating various social information. The conventional MF model is adapted by integrating the constructed UIR network for user recommendation.

Details

Internet Research, vol. 31 no. 6
Type: Research Article
ISSN: 1066-2243

Keywords

Article
Publication date: 19 January 2015

Guanjun Bao, Kun Li, Sheng Xu, Pengcheng Huang, Luan Wu and Qinghua Yang

This paper aims to avoid the precise modeling and controlling problems of rigid structures of hand recovery device, by proposing a hand rehabilitator based on flexible pneumatic…

Abstract

Purpose

This paper aims to avoid the precise modeling and controlling problems of rigid structures of hand recovery device, by proposing a hand rehabilitator based on flexible pneumatic actuator with its safety and adaptability.

Design/methodology/approach

The hand rehabilitator is designed based on a flexible pneumatic bending joint. The recovery training program for an injured finger is developed via forearm sEMG (surface electromyogram) sampling, analysis, classification and motion consciousness identification. Four typical movement models of the index finger and middle finger were defined and the corresponding sEMG signals were sampled. After simulation and comparative analysis, autoregressive (AR) model back propagation (BP) network was selected for sEMG analysis and hand recovery planning because of its best recognition performance. A verification test was designed and the results showed that the soft hand rehabilitator and recovery conception are feasible.

Findings

AR model BP network can identify the index finger and middle finger movement intention via an sEMG analysis. The developed flexible pneumatic hand rehabilitator is safe and suitable for finger recovering therapy.

Research limitations/implications

Because of the limitation of experimental samples, the prototype rehabilitator of this work may lack generalizability for other situations. Therefore, for further study and application, systematic structure revising, experiments, data and training are necessary to improve the performance.

Practical implications

The paper includes implications for the development and application of a new style, safe and dexterous hand rehabilitator.

Originality/value

The paper tries a new approach to design a safe, flexible and easily controlled hand rehabilitator.

Details

Industrial Robot: An International Journal, vol. 42 no. 1
Type: Research Article
ISSN: 0143-991X

Keywords

Article
Publication date: 19 October 2015

Mingyu Gao, Da Chen, Yuxiang Yang and Zhiwei He

The purpose of this paper is to propose a new trajectory planning algorithm for industrial robots, which can let the robots move through a desired spatial trajectory, avoid…

Abstract

Purpose

The purpose of this paper is to propose a new trajectory planning algorithm for industrial robots, which can let the robots move through a desired spatial trajectory, avoid colliding with other objects and achieve accurate movements. Trajectory planning algorithms are the soul of motion control of industrial robots. A predefined space trajectory can let the robot move through the desired spatial coordinates, avoid colliding with other objects and achieve accurate movements.

Design/methodology/approach

The mathematical expressions of the proposed algorithm are deduced. The speed control, position control and orientation control strategies are realized and verified with simulations, and then implemented on a six degrees of freedom (6-DOF) industrial robot platform.

Findings

A fixed-distance trajectory planning algorithm based on Cartesian coordinates was presented. The linear trajectory, circular trajectory, helical trajectory and parabolic trajectory in Cartesian coordinates were implemented on the 6-DOF industrial robot.

Originality/value

A simple and efficient algorithm is proposed. Enrich the kind of trajectory which the industrial robot can realize. In addition, the industrial robot can move more concisely, smoothly and precisely.

Details

Industrial Robot: An International Journal, vol. 42 no. 6
Type: Research Article
ISSN: 0143-991X

Keywords

Abstract

Details

International Journal of Numerical Methods for Heat & Fluid Flow, vol. 25 no. 7
Type: Research Article
ISSN: 0961-5539

Abstract

Details

Teacher Education in the Wake of Covid-19
Type: Book
ISBN: 978-1-80455-462-3

Article
Publication date: 14 January 2014

Yunfeng Liu, Wenqing Liao, Guangsheng Jin, Quanming Yang and Wei Peng

– The purpose is to realize precise apicoectomy with less surgical risk and improved quality and efficiency.

Abstract

Purpose

The purpose is to realize precise apicoectomy with less surgical risk and improved quality and efficiency.

Design/methodology/approach

First, the procedure of precise apicoectomy based on additive manufacturing (AM) and digital design is proposed. With CT images of the patient's oral, a 3D model of alveolar bone and teeth is reconstructed, and based on this model, the infected tissue and enclosed root tip can be determined. Thus, a surgical plan can be created based on clear anatomical relationships and minimal negative constraints, which will then determine the drill position, direction and depth, as well as the resection length of root tip. With this plan, a surgical guide design is performed via a composite model from reversed plaster models and hard tissue models from CT, and accessory tools including drill with stop plane and handle are also selected. With the surgical guide, the virtual plan in the computer can be realized in the clinic.

Findings

With this methodology, the dentist can perform root-end resection with greater accuracy, save more than 30 percent of operatory time, and the discomfort to the patient is reduced to a minimum.

Practical implications

The proposed methodology has been used in ten cases for root-end resections. In fact, this method of designing a computer-based treatment plan with a 3D model of a patient and applying it in the clinic through guiding tools can be used in other surgeries, such as orthognathic surgery or osteotomy.

Originality/value

This case report illustrates that with AM and digital design methods, optimal operational plans can be designed and realized for apicoectomy, and the quality and efficiency of clinical surgery are greatly improved compared with conventional methods.

Details

Rapid Prototyping Journal, vol. 20 no. 1
Type: Research Article
ISSN: 1355-2546

Keywords

Article
Publication date: 11 November 2013

Zhong Li, Liang Li, Fengyuan Zou and Yunchu Yang

– The purpose of this paper is to present a novel method of 3D foot and shoe model matching based on oriented bounding box (OBB) and axis-aligned bounding box (AABB).

Abstract

Purpose

The purpose of this paper is to present a novel method of 3D foot and shoe model matching based on oriented bounding box (OBB) and axis-aligned bounding box (AABB).

Design/methodology/approach

The paper first calculates their OBBs of foot and shoe models; aligns three axial directions of their OBBs to be parallel to three axes of world coordinate system. Then, computes their AABBs of foot and shoe models, translates the center of the bottom face of the foot's AABB to that of the shoe's AABB.

Findings

After the matching, the shoe model could be larger or locally smaller than the foot model. The paper finally adjusts the size of shoe model according to the distance difference.

Originality/value

Experimental results show that this method is simple and feasible which can effectively realize the matching between foot and shoe models.

Details

International Journal of Clothing Science and Technology, vol. 25 no. 5
Type: Research Article
ISSN: 0955-6222

Keywords

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