Esophageal cancer is one of the fastest rising types of cancers in China. The Kazak nationality is the highest-risk group in Xinjiang. In this work, an effective computer-aided diagnostic system is developed to assist physicians in interpreting digital X-ray image features and improving the quality of diagnosis. The modules of the proposed system include image preprocessing, feature extraction, feature selection, image classification, and performance evaluation. 300 original esophageal X-ray images were resized to a region of interest and then enhanced by the median filter and histogram equalization method. 37 features from textural, frequency, and complexity domains were extracted. Both sequential forward selection and principal component analysis methods were employed to select the discriminative features for classification. Then, support vector machine and K-nearest neighbors were applied to classify the esophageal cancer images with respect to their specific types. The classification performance was evaluated in terms of the area under the receiver operating characteristic curve, accuracy, precision, and recall, respectively. Experimental results show that the classification performance of the proposed system outperforms the conventional visual inspection approaches in terms of diagnostic quality and processing time. Therefore, the proposed computer-aided diagnostic system is promising for the diagnostics of esophageal cancer.

Fang Yang

Murat Hamit

Chuan B. Yan

Juan Yao

Abdugheni Kutluk

Xi M. Kong

Sui X. Zhang

Feature Extraction and Classification on Esophageal X-Ray Images of Xinjiang Kazak Nationality

The healthcare industry has generated large amounts of data, and analyzing these has emerged as an important problem in recent years. The MapReduce programming model has been successfully used for big data analytics. However, data skew invariably occurs in big data analytics and seriously affects efficiency. To overcome the data skew problem in MapReduce, we have in the past proposed a data processing algorithm called Partition Tuning-based Skew Handling (PTSH). In comparison with the one-stage partitioning strategy used in the traditional MapReduce model, PTSH uses a two-stage strategy and the partition tuning method to disperse key-value pairs in virtual partitions and recombines each partition in case of data skew. The robustness and efficiency of the proposed algorithm were tested on a wide variety of simulated datasets and real healthcare datasets. The results showed that PTSH algorithm can handle data skew in MapReduce efficiently and improve the performance of MapReduce jobs in comparison with the native Hadoop, Closer, and locality-aware and fairness-aware key partitioning (LEEN). We also found that the time needed for rule extraction can be reduced significantly by adopting the PTSH algorithm, since it is more suitable for association rule mining (ARM) on healthcare data.

Yufei Gao

Yanjie Zhou

Bing Zhou

Lei Shi

Jiacai Zhang

Handling Data Skew in MapReduce Cluster by Using Partition Tuning

Emergency departments (EDs) are seeking ways to utilize existing resources more efficiently as they face rising numbers of patient visits. This study explored the impact on patient wait times and nursing resource demand from the addition of a fast track, or separate unit for low-acuity patients, in the ED using a queue-based Monte Carlo simulation in MATLAB. The model integrated principles of queueing theory and expanded the discrete event simulation to account for time-based arrival rates. Additionally, the ED occupancy and nursing resource demand were modeled and analyzed using the Emergency Severity Index (ESI) levels of patients, rather than the number of beds in the department. Simulation results indicated that the addition of a separate fast track with an additional nurse reduced overall median wait times by 35.8&#x2009;&#x00B1;&#x2009;2.2 percent and reduced average nursing resource demand in the main ED during hours of operation. This novel modeling approach may be easily disseminated and informs hospital decision-makers of the impact of implementing a fast track or similar system on both patient wait times and acuity-based nursing resource demand.

Kristin Fitzgerald

Lori Pelletier

Martin A. Reznek

A Queue-Based Monte Carlo Analysis to Support Decision Making for Implementation of an Emergency Department Fast Track

Objective. To investigate and share the major challenges and experiences of building a regional health information exchange system in China in the context of health reform. Methods. This study used interviews, focus groups, a field study, and a literature review to collect insights and analyze data. The study examined Xinjin&#x2019;s approach to developing and implementing a health information exchange project, using exchange usage data for analysis. Results. Within three years and after spending approximately $2.4 million (15 million RMB), Xinjin County was able to build a complete, unified, and shared information system and many electronic health record components to integrate and manage health resources for 198 health institutions in its jurisdiction, thus becoming a model of regional health information exchange for facilitating health reform. Discussion. Costs, benefits, experiences, and lessons were discussed, and the unique characteristics of the Xinjin case and a comparison with US cases were analyzed. Conclusion. The Xinjin regional health information exchange system is different from most of the others due to its government-led, government-financed approach. Centralized and coordinated efforts played an important role in its operation. Regional health information exchange systems have been proven critical for meeting the global challenges of health reform.

Jianbo Lei

Dong Wen

Xingting Zhang

Jiayu Li

Haiying Lan

Qun Meng

Dean F. Sittig

Enabling Health Reform through Regional Health Information Exchange: A Model Study from China

We present a system for data-driven therapy decision support based on techniques from the field of recommender systems. Two methods for therapy recommendation, namely, Collaborative Recommender and Demographic-based Recommender, are proposed. Both algorithms aim to predict the individual response to different therapy options using diverse patient data and recommend the therapy which is assumed to provide the best outcome for a specific patient and time, that is, consultation. The proposed methods are evaluated using a clinical database incorporating patients suffering from the autoimmune skin disease psoriasis. The Collaborative Recommender proves to generate both better outcome predictions and recommendation quality. However, due to sparsity in the data, this approach cannot provide recommendations for the entire database. In contrast, the Demographic-based Recommender performs worse on average but covers more consultations. Consequently, both methods profit from a combination into an overall recommender system.

Felix Gr&#x00E4;&#x00DF;er

Stefanie Beckert

Denise K&#x00FC;ster

Jochen Schmitt

Susanne Abraham

Hagen Malberg

Sebastian Zaunseder

Therapy Decision Support Based on Recommender System Methods

Background. The measurement of the functional range of motion (FROM) of lower limb joints is an essential parameter for gait analysis especially in evaluating rehabilitation programs. Aim. To develop a simple, reliable, and affordable mechanical goniometer (MGR) for gait analysis, with six-degree freedom to dynamically assess lower limb joint angles. Design. Randomized control trials, in which a new MGR was developed for the measurements of FROM of lower limb joints. Setting. Reliability of the designed MGR was evaluated and validated by a motion analysis system (MAS). Population. Thirty healthy subjects participated in this study. Methods. Reliability and validity of the new MGR were tested by intraclass correlation coefficient (ICC), Bland-Altman plots, and linear correlation analysis. Results. The MGR has good inter- and intrarater reliability and validity with <svg xmlns:xlink="http://www.w3.org/1999/xlink" xmlns="http://www.w3.org/2000/svg" style="vertical-align:-1.11981pt" id="M1" height="9.88621pt" version="1.1" viewBox="-0.0498162 -8.7664 58.5274 9.88621" width="58.5274pt"><g transform="matrix(.013,0,0,-0.013,0,0)"><path id="g121-71" d="M303 0V28C221 34 213 39 213 125V525C213 610 221 616 303 622V650H38V622C120 616 128 610 128 525V125C128 40 120 34 38 28V0H303Z"/></g><g transform="matrix(.013,0,0,-0.013,4.276,0)"><path id="g121-65" d="M614 175C564 76 510 21 408 21C256 21 146 149 146 336C146 488 235 629 402 629C510 629 570 586 597 480L626 488C620 541 614 582 606 638C578 643 510 665 429 665C206 665 44 527 44 316C44 157 153 -15 402 -15C474 -15 558 5 586 11C604 45 629 119 643 165L614 175Z"/></g><g transform="matrix(.013,0,0,-0.013,13.013,0)"><use xlink:href="#g121-65"/></g><g transform="matrix(.013,0,0,-0.013,25.29,0)"><path id="g117-94" d="M531 285V335L57 550V494L473 310L57 127V71L531 285ZM531 -40V10H57V-40H531Z"/></g><g transform="matrix(.013,0,0,-0.013,36.552,0)"><path id="g113-49" d="M241 635C89 635 35 457 35 312C35 153 89 -12 240 -12C390 -12 443 166 443 312C443 466 390 635 241 635ZM238 602C329 602 354 454 354 312C354 172 330 22 240 22C152 22 124 173 124 313S148 602 238 602Z"/></g><g transform="matrix(.013,0,0,-0.013,42.792,0)"><path id="g113-47" d="M113 -12C146 -12 170 11 170 46C170 78 146 103 114 103S58 78 58 46C58 11 82 -12 113 -12Z"/></g><g transform="matrix(.013,0,0,-0.013,45.756,0)"><path id="g113-58" d="M244 635C114 635 38 519 38 422C38 317 111 240 217 240C236 240 255 244 277 256L345 292C311 140 203 39 59 15L64 -15C89 -15 150 -5 204 17C339 72 440 202 440 386C440 521 368 635 244 635ZM228 602C326 602 352 479 352 390C352 370 351 347 348 324C327 308 293 296 258 296C174 296 124 369 124 458C124 517 152 602 228 602Z"/></g><g transform="matrix(.013,0,0,-0.013,51.998,0)"><path id="g113-52" d="M285 378C315 398 338 416 353 432C373 451 384 474 384 503C384 579 325 635 236 635H235C182 635 136 610 108 579L65 516L85 496C110 533 150 575 205 575C258 575 300 543 300 481C300 407 232 369 141 339L147 310C163 315 188 321 211 321C268 321 338 284 338 192C338 94 288 40 217 40C160 40 119 68 93 91C85 98 77 97 69 91C60 84 47 71 46 58C44 46 48 35 62 22C75 10 116 -12 162 -12C234 -12 424 62 424 224C424 297 373 359 285 376V378Z"/></g></svg> (for both). Moreover, measurements made by MGR and MAS were comparable and repeatable with each other, as confirmed by Bland-Altman plots. Furthermore, a very high degree of linear correlation (<svg xmlns:xlink="http://www.w3.org/1999/xlink" xmlns="http://www.w3.org/2000/svg" style="vertical-align:-1.11981pt" id="M2" height="9.75571pt" version="1.1" viewBox="-0.0498162 -8.6359 44.9698 9.75571" width="44.9698pt"><g transform="matrix(.013,0,0,-0.013,0,0)"><path id="g113-83" d="M610 18C585 26 567 34 540 68C517 97 499 128 476 171C452 215 425 276 413 304C496 332 570 394 570 494C570 555 545 595 509 619S419 650 364 650H139L133 622C216 615 219 612 203 527L129 132C112 40 105 36 23 28L17 0H279L285 28C199 34 194 40 211 132L239 284H284C320 284 334 275 351 236C374 182 394 140 420 93C459 23 495 -1 592 -8H600L610 18ZM480 485C480 424 449 372 403 342C374 323 338 316 293 316H245L291 562C296 589 301 601 311 608S337 618 358 618C432 618 480 575 480 485Z"/></g><g transform="matrix(.013,0,0,-0.013,11.783,0)"><use xlink:href="#g117-94"/></g><g transform="matrix(.013,0,0,-0.013,23.046,0)"><use xlink:href="#g113-49"/></g><g transform="matrix(.013,0,0,-0.013,29.286,0)"><use xlink:href="#g113-47"/></g><g transform="matrix(.013,0,0,-0.013,32.25,0)"><use xlink:href="#g113-58"/></g><g transform="matrix(.013,0,0,-0.013,38.491,0)"><path id="g113-51" d="M412 140C382 77 369 73 315 73H129L270 222C362 320 402 379 402 466C402 571 322 635 234 635C177 635 130 609 99 576L42 495L64 475C90 514 133 568 201 568C274 568 318 519 318 435C318 349 255 267 193 193C144 135 87 78 32 23V0H405C417 45 427 89 440 131L412 140Z"/></g></svg> for all joint angle measurements) was found between the lower limb joint angles measured by MGR and MAS. Conclusion. A simple, reliable, and affordable MGR has been designed and developed to aid clinical assessment and treatment evaluation of gait disorders.

Congo Tak-Shing Ching

Su-Yu Liao

Teng-Yun Cheng

Chih-Hsiu Cheng

Tai-Ping Sun

Yan-Dong Yao

Chin-Sung Hsiao

Kang-Ming Chang

A Mechanical Sensor Designed for Dynamic Joint Angle Measurement

Facetectomy is an important intervention for spinal stenosis but may lead to spinal instability. Biomechanical knowledge for facetectomy can be beneficial when deciding whether fusion is necessary. Therefore, the aim of this study was to investigate the biomechanical effect of different grades of facetectomy. A three-dimensional nonlinear finite element model of L3&#x2013;L5 was constructed. The mobility of the model and the intradiscal pressure (IDP) of L4-L5 for standing were inside the data from the literature. The effect of graded facetectomy on intervertebral rotation, IDP, facet joint forces, and maximum von Mises equivalent stresses in the annuli was analyzed under flexion, extension, left/right lateral bending, and left/right axial rotation. Compared with the intact model, under extension, unilateral facetectomy increased the range of intervertebral rotation (IVR) by 11.7&#x25; and IDP by 10.7&#x25;, while the bilateral facetectomy increased IVR by 40.7&#x25; and IDP by 23.6&#x25;. Under axial rotation, the unilateral facetectomy and the bilateral facetectomy increased the IVR by 101.3&#x25; and 354.3&#x25;, respectively, when turned to the right and by 1.1&#x25; and 265.3&#x25;, respectively, when turned to the left. The results conclude that, after unilateral and bilateral facetectomy, care must be taken when placing the spine into extension and axial rotation posture from the biomechanical point of view.

Zhi-li Zeng

Rui Zhu

Yang-chun Wu

Wei Zuo

Yan Yu

Jian-jie Wang

Li-ming Cheng

Effect of Graded Facetectomy on Lumbar Biomechanics

The purpose of this study was to characterize cardiovascular tissue components and analyze the different tissue properties for predicting coronary vulnerable plaque from intravascular ultrasound (IVUS) images. For this purpose, sequential IVUS image frames were obtained from human coronary arteries using 20&#x2009;MHz catheters. The plaque regions between the intima and media-adventitial borders were manually segmented in all IVUS images. Tissue components of the plaque regions were classified into having fibrous tissue (FT), fibrofatty tissue (FFT), necrotic core (NC), or dense calcium (DC). The media area and lumen diameter were also estimated simultaneously. In addition, the external elastic membrane (EEM) was computed to predict the vulnerable plaque after the tissue characterization. The reliability of manual segmentation was validated in terms of inter- and intraobserver agreements. The quantitative results found that the FT and the media as well as the NC would be good indicators for predicting vulnerable plaques in IVUS images. In addition, the lumen was not suitable for early diagnosis of vulnerable plaque because of the low significance compared to the other vessel parameters. To predict vulnerable plaque rupture, future study should have additional experiments using various tissue components, such as the EEM, FT, NC, and media.

Ju Hwan Lee

Yoo Na Hwang

Ga Young Kim

Eun Seok Shin

Sung Min Kim

Analysis of Cardiovascular Tissue Components for the Diagnosis of Coronary Vulnerable Plaque from Intravascular Ultrasound Images

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Journal of Healthcare Engineering provides a vehicle for the exchange of advanced knowledge, emerging technologies, and innovative ideas related to all aspects of engineering involved in healthcare delivery processes and systems.

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Journal of Healthcare Engineering - Table of contents 2017

Journal of Healthcare Engineering | Hindawi

title

Journal of Healthcare Engineering provides a vehicle for the exchange of advanced knowledge, emerging technologies, and innovative ideas related to all aspects of engineering involved in healthcare delivery processes and systems.

Journal of Healthcare Engineering