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1.
Sensors (Basel) ; 21(19)2021 Sep 22.
Artigo em Inglês | MEDLINE | ID: mdl-34640651

RESUMO

The automatic detection of the thread roll's margin is one of the kernel problems in the textile field. As the traditional detection method based on the thread's tension has the disadvantages of high cost and low reliability, this paper proposes a technology that installs a camera on a mobile robot and uses computer vision to detect the thread roll's margin. Before starting, we define a thread roll's margin as follows: The difference between the thread roll's radius and the bobbin's radius. Firstly, we capture images of the thread roll's end surface. Secondly, we obtain the bobbin's image coordinates by calculating the image's convolutions with a Circle Gradient Operator. Thirdly, we fit the thread roll and bobbin's contours into ellipses, and then delete false detections according to the bobbin's image coordinates. Finally, we restore every sub-image of the thread roll by a perspective transformation method, and establish the conversion relationship between the actual size and pixel size. The difference value of the two concentric circles' radii is the thread roll's margin. However, there are false detections and these errors may be more than 19.4 mm when the margin is small. In order to improve the precision and delete false detections, we use deep learning to detect thread roll and bobbin's radii and then can calculate the thread roll's margin. After that, we fuse the two results. However, the deep learning method also has some false detections. As such, in order to eliminate the false detections completely, we estimate the thread roll's margin according to thread consumption speed. Lastly, we use a Kalman Filter to fuse the measured value and estimated value; the average error is less than 5.7 mm.


Assuntos
Computadores , Visão Ocular , Reprodutibilidade dos Testes
2.
Sensors (Basel) ; 21(19)2021 Sep 23.
Artigo em Inglês | MEDLINE | ID: mdl-34640669

RESUMO

This paper presents a posture recognition system aimed at detecting sitting postures of a wheelchair user. The main goals of the proposed system are to identify and inform irregular and improper posture to prevent sitting-related health issues such as pressure ulcers, with the potential that it could also be used for individuals without mobility issues. In the proposed monitoring system, an array of 16 screen printed pressure sensor units was employed to obtain pressure data, which are sampled and processed in real-time using read-out electronics. The posture recognition was performed for four sitting positions: right-, left-, forward- and backward leaning based on k-nearest neighbors (k-NN), support vector machines (SVM), random forest (RF), decision tree (DT) and LightGBM machine learning algorithms. As a result, a posture classification accuracy of up to 99.03 percent can be achieved. Experimental studies illustrate that the system can provide real-time pressure distribution value in the form of a pressure map on a standard PC and also on a raspberry pi system equipped with a touchscreen monitor. The stored pressure distribution data can later be shared with healthcare professionals so that abnormalities in sitting patterns can be identified by employing a post-processing unit. The proposed system could be used for risk assessments related to pressure ulcers. It may be served as a benchmark by recording and identifying individuals' sitting patterns and the possibility of being realized as a lightweight portable health monitoring device.


Assuntos
Cadeiras de Rodas , Computadores , Humanos , Aprendizado de Máquina , Postura , Postura Sentada
3.
Sensors (Basel) ; 21(19)2021 Sep 23.
Artigo em Inglês | MEDLINE | ID: mdl-34640673

RESUMO

Rice quality assessment is essential for meeting high-quality standards and consumer demands. However, challenges remain in developing cost-effective and rapid techniques to assess commercial rice grain quality traits. This paper presents the application of computer vision (CV) and machine learning (ML) to classify commercial rice samples based on dimensionless morphometric parameters and color parameters extracted using CV algorithms from digital images obtained from a smartphone camera. The artificial neural network (ANN) model was developed using nine morpho-colorimetric parameters to classify rice samples into 15 commercial rice types. Furthermore, the ANN models were deployed and evaluated on a different imaging system to simulate their practical applications under different conditions. Results showed that the best classification accuracy was obtained using the Bayesian Regularization (BR) algorithm of the ANN with ten hidden neurons at 91.6% (MSE = <0.01) and 88.5% (MSE = 0.01) for the training and testing stages, respectively, with an overall accuracy of 90.7% (Model 2). Deployment also showed high accuracy (93.9%) in the classification of the rice samples. The adoption by the industry of rapid, reliable, and accurate methods, such as those presented here, may allow the incorporation of different morpho-colorimetric traits in rice with consumer perception studies.


Assuntos
Oryza , Teorema de Bayes , Computadores , Aprendizado de Máquina , Percepção
4.
Sensors (Basel) ; 21(19)2021 Sep 28.
Artigo em Inglês | MEDLINE | ID: mdl-34640796

RESUMO

The use of inertial measurement units (IMUs) is a low-cost alternative for measuring joint angles. This study aims to present a low-cost open-source measurement system for joint angle estimation. The system is modular and has hardware and software. The hardware was developed using a low-cost IMU and microcontroller. The IMU data analysis software was developed in Python and has three fusion filters: Complementary Filter, Kalman Filter, and Madgwick Filter. Three experiments were performed for the proof of concept of the system. First, we evaluated the knee joint of Lokomat, with a predefined average range of motion (ROM) of 60∘. In the second, we evaluated our system in a real scenario, evaluating the knee of a healthy adult individual during gait. In the third experiment, we evaluated the software using data from gold standard devices, comparing the results of our software with Ground Truth. In the evaluation of the Lokomat, our system achieved an average ROM of 58.28∘, and during evaluation in a real scenario it achieved an average ROM of 44.62∘. In comparing our software with Ground Truth, we achieved a root-mean-square error of 0.04 and a mean average percentage error of 2.95%. These results encourage the use of this system in other scenarios.


Assuntos
Marcha , Articulação do Joelho , Fenômenos Biomecânicos , Computadores , Amplitude de Movimento Articular
5.
Clin Oral Implants Res ; 32 Suppl 21: 303-317, 2021 Oct.
Artigo em Inglês | MEDLINE | ID: mdl-34642994

RESUMO

AIM: To study the time and costs involved with computer-assisted versus non-computer-assisted implant planning and placement. MATERIAL AND METHODS: Based on the PICO question, "In patients receiving dental implants, is computer-assisted implant planning and surgery (CAIPS) compared to non-computer-assisted implant planning and surgery (non-CAIPS) beneficial in terms of treatment related costs and time involved?", a search path was created to perform an electronic search in the databases PubMed, PubMed Central, EMBASE, and Cochrane. The publication period of eligible publications extended from 01.01.2005 to 04.05.2020. Four independent reviewers reviewed the literature to identify studies that met the eligibility inclusion criteria. A further manual search of articles was performed, and gray literature was excluded. Corresponding authors of potentially eligible manuscripts were contacted for further information. RESULTS: Of the 1354 retrieved titles after the search were screened. Thirty-one articles have been identified to read the full text, resulting in four articles to be analyzed for the present review all of which were RCTs. In total, 182 partially and completely edentulous patients were treated with 416 implants following either non-computer-assisted or computer-assisted implant planning and surgery to determine the duration of the single working steps and the financial aspects of the different procedures. CONCLUSIONS: When evaluating the time and costs involved with the diagnostic and planning procedures in computer-assisted implant planning and surgery workflow protocols, one can summarize that these are higher than in the non-computer-assisted workflow protocols. The time involved with the procedures appears to be the driving factor when it comes to economic considerations. On the basis of the conclusions, also the time for the prosthetic restoration should be taken into account.


Assuntos
Implantes Dentários , Cirurgia Assistida por Computador , Computadores , Implantação Dentária Endo-Óssea , Prótese Dentária Fixada por Implante , Humanos
6.
Curr Protoc ; 1(10): e255, 2021 Oct.
Artigo em Inglês | MEDLINE | ID: mdl-34610215

RESUMO

Tracking animal behavior by video is one of the most common tasks in neuroscience. Previously, we have validated ezTrack, a free, flexible, and easy-to-use software for the analysis of animal behavior. ezTrack's Location Tracking Module can be used for the positional analysis of an individual animal and is applicable to a wide range of behavioral tasks. Separately, ezTrack's Freeze Analysis Module is designed for the analysis of defensive freezing behavior. ezTrack supports a range of desirable tools, including options for cropping and masking portions of the field of view, defining regions of interest, producing summary data for specified portions of time, algorithms to remove the influence of electrophysiology cables and other tethers, batch processing of multiple videos, and video down-sampling. Moreover, ezTrack produces a range of interactive plots and visualizations to promote users' confidence in their results. In this protocols paper, we provide step-by-step instructions for the use of ezTrack, from tips for recording behavior to instructions for using the software for video analysis. © 2021 Wiley Periodicals LLC. Basic Protocol 1: Software environment installation Basic Protocol 2: Using the Location Tracking Module Basic Protocol 3: Using the Freeze Analysis Module.


Assuntos
Algoritmos , Software , Animais , Comportamento Animal , Computadores , Fenômenos Eletrofisiológicos
7.
Zhongguo Yi Liao Qi Xie Za Zhi ; 45(5): 497-502, 2021 Sep 30.
Artigo em Chinês | MEDLINE | ID: mdl-34628760

RESUMO

In order to reduce the working intensity of medical staff in inspecting patients during traditional infusion, a remote monitoring system for intravenous infusion is designed for solving the problem of delay in handling treatment during infusion process and to reduce the incidence of medical accidents. The system uses Visual Basic.NET language to develop the upper computer platform for infusion monitoring. It uses the Arduino control board and infrared photoelectric sensor to form a monitoring device to detect relevant information. At the same time, it uses Zigbee wireless sensing technology to transmit data and upload it to the software platform. The results show that the system can receive data from multiple monitoring terminal devices in the upper computer platform application interface at the same time. It can display the data in the nurse station in a graphical way, and perform alarm warning and information storage during the infusion process. The infusion monitoring system can observe the monitoring situation in real time, reduce the workload of medical staff, and further improve the operating efficiency and safety of the hospital.


Assuntos
Eletrocardiografia , Tecnologia sem Fio , Computadores , Desenho de Equipamento , Humanos , Monitorização Fisiológica
8.
Artigo em Chinês | MEDLINE | ID: mdl-34628830

RESUMO

Objective:To identified the feasibility and normal range of cone beam computer tomography(CBCT) in the measurement of temporal bone. Methods:15 formalin fixed human cadaver head specimens were scanned by CBCT, high resolution CT, and Micro CT, respectively. Morphological parameter measurements of the middle and inner ear structures including ossicular chain, cochlea, semicircular canal and facial nerve were performed, and the results measured by the three scanning methods were compared. Results:None of the parameters measured by the three scanning methods were statistically significant except the thickness of stapes footplate(P<0.01) and the diameter of cochlear basal turn(P<0.01). CBCT was superior in detecting facial nerve bony canal dehiscence. Conclusion:CBCT has the advantages of short scanning time, low radiation dose and high resolution. It can accurately display the morphological characteristics of the temporal bone structures, and is a reliable evaluation method for otological surgery.


Assuntos
Tomografia Computadorizada de Feixe Cônico , Osso Temporal , Computadores , Orelha Média , Humanos , Canais Semicirculares/diagnóstico por imagem , Osso Temporal/diagnóstico por imagem
9.
Acta Ortop Mex ; 35(1): 23-27, 2021.
Artigo em Espanhol | MEDLINE | ID: mdl-34480435

RESUMO

INTRODUCTION: Total navigated knee replacement uses a computer-guided system, which provides immediate information on pre-cut trans-operative conditions of the knee, in relation to pelvic limb alignment. MATERIAL AND METHODS: Observational, descriptive study conducted from March 2003 to February 2019. Total bilateral knee replacement was performed at the same time surgically by a surgeon, evaluating function and pain on the WOMAC, EVA, and range of motion scores of both knees. Two groups of patients were studied: the first represents presurgical and the second post-surgical. Student's t-test and 2 were applied for statistical analysis. RESULTS: 31 patients (62 prostheses), 83.9% of the female sex and 16.1% male, average age 67.32 years, average follow-up 6.55 years (± 3.8) were studied. It was identified that 100% of the patients in both knees have a deviation between 0o and 2o measured in the mechanical axis. The WOMAC scale showed an average of 22.71 ± 3.34 presurgical and 4.16 ± 1.84) post-surgical, with statistically significant differences. The average analog visual scale was 9.06 ± 0.814 presurgical and 2.35 ± 1.427 post-surgical. CONCLUSIONS: This technique is reliable, safe and satisfactory. Excellent clinical and radiographic results were evident regarding the positioning of prosthetic components.


Assuntos
Artroplastia do Joelho , Osteoartrite do Joelho , Cirurgia Assistida por Computador , Idoso , Computadores , Feminino , Humanos , Articulação do Joelho/cirurgia , Masculino , Duração da Cirurgia , Osteoartrite do Joelho/cirurgia , Resultado do Tratamento
10.
World J Gastroenterol ; 27(31): 5232-5246, 2021 Aug 21.
Artigo em Inglês | MEDLINE | ID: mdl-34497447

RESUMO

BACKGROUND: Artificial intelligence in colonoscopy is an emerging field, and its application may help colonoscopists improve inspection quality and reduce the rate of missed polyps and adenomas. Several deep learning-based computer-assisted detection (CADe) techniques were established from small single-center datasets, and unrepresentative learning materials might confine their application and generalization in wide practice. Although CADes have been reported to identify polyps in colonoscopic images and videos in real time, their diagnostic performance deserves to be further validated in clinical practice. AIM: To train and test a CADe based on multicenter high-quality images of polyps and preliminarily validate it in clinical colonoscopies. METHODS: With high-quality screening and labeling from 55 qualified colonoscopists, a dataset consisting of over 71000 images from 20 centers was used to train and test a deep learning-based CADe. In addition, the real-time diagnostic performance of CADe was tested frame by frame in 47 unaltered full-ranged videos that contained 86 histologically confirmed polyps. Finally, we conducted a self-controlled observational study to validate the diagnostic performance of CADe in real-world colonoscopy with the main outcome measure of polyps per colonoscopy in Changhai Hospital. RESULTS: The CADe was able to identify polyps in the test dataset with 95.0% sensitivity and 99.1% specificity. For colonoscopy videos, all 86 polyps were detected with 92.2% sensitivity and 93.6% specificity in frame-by-frame analysis. In the prospective validation, the sensitivity of CAD in identifying polyps was 98.4% (185/188). Folds, reflections of light and fecal fluid were the main causes of false positives in both the test dataset and clinical colonoscopies. Colonoscopists can detect more polyps (0.90 vs 0.82, P < 0.001) and adenomas (0.32 vs 0.30, P = 0.045) with the aid of CADe, particularly polyps < 5 mm and flat polyps (0.65 vs 0.57, P < 0.001; 0.74 vs 0.67, P = 0.001, respectively). However, high efficacy is not realized in colonoscopies with inadequate bowel preparation and withdrawal time (P = 0.32; P = 0.16, respectively). CONCLUSION: CADe is feasible in the clinical setting and might help endoscopists detect more polyps and adenomas, and further confirmation is warranted.


Assuntos
Pólipos do Colo , Aprendizado Profundo , Inteligência Artificial , Pólipos do Colo/diagnóstico por imagem , Colonoscopia , Computadores , Humanos
11.
Sensors (Basel) ; 21(17)2021 Aug 24.
Artigo em Inglês | MEDLINE | ID: mdl-34502579

RESUMO

In this paper, Computer Vision (CV) sensing technology based on Convolutional Neural Network (CNN) is introduced to process topographic maps for predicting wireless signal propagation models, which are applied in the field of forestry security monitoring. In this way, the terrain-related radio propagation characteristic including diffraction loss and shadow fading correlation distance can be predicted or extracted accurately and efficiently. Two data sets are generated for the two prediction tasks, respectively, and are used to train the CNN. To enhance the efficiency for the CNN to predict diffraction losses, multiple output values for different locations on the map are obtained in parallel by the CNN to greatly boost the calculation speed. The proposed scheme achieved a good performance in terms of prediction accuracy and efficiency. For the diffraction loss prediction task, 50% of the normalized prediction error was less than 0.518%, and 95% of the normalized prediction error was less than 8.238%. For the correlation distance extraction task, 50% of the normalized prediction error was less than 1.747%, and 95% of the normalized prediction error was less than 6.423%. Moreover, diffraction losses at 100 positions were predicted simultaneously in one run of CNN under the settings in this paper, for which the processing time of one map is about 6.28 ms, and the average processing time of one location point can be as low as 62.8 us. This paper shows that our proposed CV sensing technology is more efficient in processing geographic information in the target area. Combining a convolutional neural network to realize the close coupling of a prediction model and geographic information, it improves the efficiency and accuracy of prediction.


Assuntos
Agricultura Florestal , Redes Neurais de Computação , Computadores , Tecnologia
12.
Sensors (Basel) ; 21(17)2021 Sep 03.
Artigo em Inglês | MEDLINE | ID: mdl-34502814

RESUMO

This work studies the feasibility of a novel two-step algorithm for infrastructure and object positioning, using pairwise distances. The proposal is based on the optimization algorithms, Scaling-by-Majorizing-a-Complicated-Function and the Limited-Memory-Broyden-Fletcher-Goldfarb-Shannon. A qualitative evaluation of these algorithms is performed for 3D positioning. As the final stage, smoothing filtering techniques are applied to estimate the trajectory, from the previously obtained positions. This approach can also be used as a synthetic gesture data generator framework. This framework is independent from the hardware and can be used to simulate the estimation of trajectories from noisy distances gathered with a large range of sensors by modifying the noise properties of the initial distances. The framework is validated, using a system of ultrasound transceivers. The results show this framework to be an efficient and simple positioning and filtering approach, accurately reconstructing the real path followed by the mobile object while maintaining low latency. Furthermore, these capabilities can be exploited by using the proposed algorithms for synthetic data generation, as demonstrated in this work, where synthetic ultrasound gesture data are generated.


Assuntos
Gestos , Análise de Escalonamento Multidimensional , Algoritmos , Computadores
13.
Sensors (Basel) ; 21(17)2021 Sep 06.
Artigo em Inglês | MEDLINE | ID: mdl-34502854

RESUMO

This paper deals with analysis of behavioural patterns in human-computer interaction. In the study, keystroke dynamics were analysed while participants were writing positive and negative opinions. A semi-experiment with 50 participants was performed. The participants were asked to recall the most negative and positive learning experiences (subject and teacher) and write an opinion about it. Keystroke dynamics were captured and over 50 diverse features were calculated and checked against the ability to differentiate positive and negative opinions. Moreover, classification of opinions was performed providing accuracy slightly above the random guess level. The second classification approach used self-report labels of pleasure and arousal and showed more accurate results. The study confirmed that it was possible to recognize positive and negative opinions from the keystroke patterns with accuracy above the random guess; however, combination with other modalities might produce more accurate results.


Assuntos
Atitude , Computadores , Humanos , Redação
14.
Artigo em Inglês | MEDLINE | ID: mdl-34501748

RESUMO

Quarantines imposed due to COVID-19 have forced the rapid implementation of e-learning, but also increased the rates of anxiety, depression, and fatigue, which relate to dramatically diminished e-learning motivation. Thus, it was deemed significant to identify e-learning motivating factors related to mental health. Furthermore, because computer programming skills are among the core competencies that professionals are expected to possess in the era of rapid technology development, it was also considered important to identify the factors relating to computer programming learning. Thus, this study applied the Learning Motivating Factors Questionnaire, the Patient Health Questionnaire-9 (PHQ-9), the Generalized Anxiety Disorder Scale-7 (GAD-7), and the Multidimensional Fatigue Inventory-20 (MFI-20) instruments. The sample consisted of 444 e-learners, including 189 computer programming e-learners. The results revealed that higher scores of individual attitude and expectation, challenging goals, clear direction, social pressure, and competition significantly varied across depression categories. The scores of challenging goals, and social pressure and competition, significantly varied across anxiety categories. The scores of individual attitude and expectation, challenging goals, and social pressure and competition significantly varied across general fatigue categories. In the group of computer programming e-learners: challenging goals predicted decreased anxiety; clear direction and challenging goals predicted decreased depression; individual attitude and expectation predicted diminished general fatigue; and challenging goals and punishment predicted diminished mental fatigue. Challenging goals statistically significantly predicted lower mental fatigue, and mental fatigue statistically significantly predicted depression and anxiety in both sample groups.


Assuntos
COVID-19 , Instrução por Computador , Ansiedade , Computadores , Depressão/epidemiologia , Humanos , SARS-CoV-2
15.
BMC Bioinformatics ; 22(1): 439, 2021 Sep 15.
Artigo em Inglês | MEDLINE | ID: mdl-34525939

RESUMO

BACKGROUND: Accurate prediction of protein tertiary structures is highly desired as the knowledge of protein structures provides invaluable insights into protein functions. We have designed two approaches to protein structure prediction, including a template-based modeling approach (called ProALIGN) and an ab initio prediction approach (called ProFOLD). Briefly speaking, ProALIGN aligns a target protein with templates through exploiting the patterns of context-specific alignment motifs and then builds the final structure with reference to the homologous templates. In contrast, ProFOLD uses an end-to-end neural network to estimate inter-residue distances of target proteins and builds structures that satisfy these distance constraints. These two approaches emphasize different characteristics of target proteins: ProALIGN exploits structure information of homologous templates of target proteins while ProFOLD exploits the co-evolutionary information carried by homologous protein sequences. Recent progress has shown that the combination of template-based modeling and ab initio approaches is promising. RESULTS: In the study, we present FALCON2, a web server that integrates ProALIGN and ProFOLD to provide high-quality protein structure prediction service. For a target protein, FALCON2 executes ProALIGN and ProFOLD simultaneously to predict possible structures and selects the most likely one as the final prediction result. We evaluated FALCON2 on widely-used benchmarks, including 104 CASP13 (the 13th Critical Assessment of protein Structure Prediction) targets and 91 CASP14 targets. In-depth examination suggests that when high-quality templates are available, ProALIGN is superior to ProFOLD and in other cases, ProFOLD shows better performance. By integrating these two approaches with different emphasis, FALCON2 server outperforms the two individual approaches and also achieves state-of-the-art performance compared with existing approaches. CONCLUSIONS: By integrating template-based modeling and ab initio approaches, FALCON2 provides an easy-to-use and high-quality protein structure prediction service for the community and we expect it to enable insights into a deep understanding of protein functions.


Assuntos
Redes Neurais de Computação , Proteínas , Sequência de Aminoácidos , Computadores , Conformação Proteica , Software
16.
Artigo em Inglês | MEDLINE | ID: mdl-34574844

RESUMO

BACKGROUND: Adolescents and ethnic subgroups have been identified at high risks of overweight and its associated complications. Although some studies have investigated overweight, obesity, nutritional status, physical activity, and associated factors among Saudi students, no studies have examined these characteristics among non-Saudi students or compared non-Saudi to Saudi adolescent students. The objective of this study was to compare differences between Saudi and non-Saudi adolescent students regarding time spent watching television, using computers, engaging in physical activity, and their food preferences. The relationships between these lifestyle behaviors and body mass index by Saudi nativity and gender were tested. METHODS: Students aged 12 to 18 years (n = 214) from various schools in Riyadh, Saudi Arabia, completed a self-administered questionnaire that included questions about demographic and anthropometric characteristics, daily after-school routine, physical activity, watching television, using computers, and food preferences. Non-parametric (Mann-Whitney U) tests assessed the statistical differences between Saudi and non-Saudi respondents, and males and females were separately tested. RESULTS: Saudi boys who reported physical activity two to five times per week, the most television time, the most computer time, and the highest frequency of eating fast food and drinking soft drinks had a significantly higher mean body mass index than the non-Saudi boys in their categories. However, there were no significant differences found between the Saudi and non-Saudi girls. CONCLUSIONS: High levels of sedentary and low levels of physical activities as well as high consumption of high-fat fast foods and high-sugar drinks threaten the health of Saudi adolescents. Cultural differences in lifestyle between Saudi and non-Saudi families should be considered when developing programs to improve knowledge, attitudes, and behaviors regarding diet quality and physical activity. The objective of this study is more important in the current situation where increased time spent on computers and mobile phones due to online teaching in schools or working from home, decreased physical activity due to precautionary lockdowns, and unchecked eating patterns while spending more time in sedentary activities in homes has become our COVID-19 pandemic lifestyle in all the age groups. A similar study should be replicated on a large scale to study the effect of this lifestyle on our lives in all the age groups.


Assuntos
COVID-19 , Preferências Alimentares , Adolescente , Índice de Massa Corporal , Controle de Doenças Transmissíveis , Computadores , Estudos Transversais , Exercício Físico , Comportamento Alimentar , Feminino , Humanos , Masculino , Pandemias , SARS-CoV-2 , Arábia Saudita , Comportamento Sedentário , Televisão
17.
Vet Clin Pathol ; 50(3): 427-441, 2021 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-34476826

RESUMO

BACKGROUND: Inaccuracy in estimating reference intervals (RIs) is a problem with small sample sizes. OBJECTIVES: This study aimed to identify the most accurate statistical methods to estimate RIs based on sample size and population distribution shape. We also studied the accuracy of sample frequency distribution histograms to retrieve the original population distribution and compared strategies based on the histogram and goodness-of-fit test. METHODS: The statistical methods that best enhanced accuracy were determined for various sample sizes (n = 20-60) and population distributions (Gaussian, log-normal, and left-skewed) were determined by repeated-measures ANOVA and posthoc analyses. Frequency distribution histograms were built from 900 samples of five different sizes randomly extracted from six simulated populations. Three reviewers classified the population distributions from visual assessments of a sample histogram, and the classification error rate was calculated. RI accuracy was compared among the strategies based on the histograms and goodness-of-fit tests. RESULTS: The parametric, nonparametric, and robust methods enhanced lower reference limit estimation accuracy for Gaussian, log-normal, and left-skewed distributions, respectively. The parametric, nonparametric bootstrap, and nonparametric methods enhanced the upper limit estimation accuracy for Gaussian, log-normal, and left-skewed distributions, respectively. Regardless of sample size, sample histogram assessments properly classified the original population distribution 71% to 93.9% of the time, depending on the reviewers. In this study, the strategy based on histograms assessed by the statistician was significantly more precise and accurate than the strategy based on the goodness-of-fit test (P < 0.001). CONCLUSIONS: A strategy based on histograms might enhance the accuracy of RI estimations. However, relevant inter-reviewer variations in histogram interpretation were detected. Factors affecting inter-reviewer variations should be further explored.


Assuntos
Computadores , Animais , Simulação por Computador , Distribuição Normal , Valores de Referência , Tamanho da Amostra
18.
JNMA J Nepal Med Assoc ; 59(240): 795-798, 2021 Aug 12.
Artigo em Inglês | MEDLINE | ID: mdl-34508490

RESUMO

Intracanal separation of nickel titanium files hinders complete shaping, cleaning, and filling of the root canal system and ultimately influences the endodontic treatment outcome. In this case report, we presented a successful broken instrument retrieval from the middle third of the mesiobuccal root canal of tooth #30 with the assistance of cone-beam computed tomograpgy based preoperative computer-assisted simulation, micro-trepan bur and micro-tube from Micro-Retrieve & Repair system and dental operative microscope. The involved tooth was then successfully cleaned, shaped and obturated followed by coronal restoration. At the three-year follow-up, tooth #30 was asymptomatic and functioned well without radiographic changes. The present case provides an example to show the robustness of computer-assisted technology in dental procedures and to show how the combination of advanced techniques can facilitate root canal therapy.


Assuntos
Dente Molar , Preparo de Canal Radicular , Computadores , Humanos , Dente Molar/diagnóstico por imagem , Dente Molar/cirurgia , Tratamento do Canal Radicular , Tomografia
19.
Comput Methods Programs Biomed ; 210: 106363, 2021 Oct.
Artigo em Inglês | MEDLINE | ID: mdl-34478913

RESUMO

BACKGROUND AND OBJECTIVE: Computer-aided diagnosis (CAD) systems promote accurate diagnosis and reduce the burden of radiologists. A CAD system for lung cancer diagnosis includes nodule candidate detection and nodule malignancy evaluation. Recently, deep learning-based pulmonary nodule detection has reached satisfactory performance ready for clinical application. However, deep learning-based nodule malignancy evaluation depends on heuristic inference from low-dose computed tomography (LDCT) volume to malignant probability, and lacks clinical cognition. METHODS: In this paper, we propose a joint radiology analysis and malignancy evaluation network called R2MNet to evaluate pulmonary nodule malignancy via the analysis of radiological characteristics. Radiological features are extracted as channel descriptor to highlight specific regions of the input volume that are critical for nodule malignancy evaluation. In addition, for model explanations, we propose channel-dependent activation mapping (CDAM) to visualize features and shed light on the decision process of deep neural networks (DNNs). RESULTS: Experimental results on the lung image database consortium image collection (LIDC-IDRI) dataset demonstrate that the proposed method achieved an area under curve (AUC) of 96.27% and 97.52% on nodule radiology analysis and nodule malignancy evaluation, respectively. In addition, explanations of CDAM features proved that the shape and density of nodule regions are two critical factors that influence a nodule to be inferred as malignant. This process conforms to the diagnosis cognition of experienced radiologists. CONCLUSION: The network inference process conforms to the diagnostic procedure of radiologists and increases the confidence of evaluation results by incorporating radiology analysis with nodule malignancy evaluation. Besides, model interpretation with CDAM features shed light on the focus regions of DNNs during the estimation of nodule malignancy probabilities.


Assuntos
Neoplasias Pulmonares , Radiologia , Nódulo Pulmonar Solitário , Computadores , Humanos , Pulmão , Neoplasias Pulmonares/diagnóstico por imagem , Interpretação de Imagem Radiográfica Assistida por Computador , Nódulo Pulmonar Solitário/diagnóstico por imagem
20.
Comput Methods Programs Biomed ; 210: 106362, 2021 Oct.
Artigo em Inglês | MEDLINE | ID: mdl-34482127

RESUMO

BACKGROUND: Electronic medical records (EMRs) are widely used, but in many cases, they are used within a network physically separated from the Internet. Multicenter clinical studies use Internet-connected electronic data capture (EDC) systems to collect data, where data entered into the EMR are manually transcribed into the EDC system. In addition, medical images for clinical research are also collected manually. Variations in EMRs and differing data structures among vendors hamper the use of data for clinical research. METHODS: We solved this problem by developing a network infrastructure for clinical research between Osaka University Hospital and affiliated hospitals in the Osaka area and introducing a clinical data collection system (CDCS). In each hospital's EMR network, we implemented a CRF reporter that accumulated data for clinical research using a template and then sent the data to a management server in the Osaka University Hospital Data Center. To organize the patient profile data and clinical laboratory data stored in each EMR for use in clinical research, the data are retrieved from the template by an interface module developed by each vendor, according to our common data output interface specification. The data entered into the CRF reporter template for clinical research are also recorded in the EMR progress notes and sent to the data management server. This network infrastructure can also be used as a medical image collection system that automatically collects images for research from PACS at each hospital. These systems are managed under common subject numbers issued by the CDCS. RESULTS: A network infrastructure was established among 19 hospitals, and a CRF reporter was incorporated into the EMR. A medical image transfer system was introduced in 13 hospitals. Since 2013, 28 clinical studies have been conducted using this system, and data for 9,987 cases have been collected as of December 31, 2020. CONCLUSION: Incorporating a CRF reporter with medical image transfer system into the EMR has proven useful for collecting research data.


Assuntos
Gerenciamento de Dados , Registros Eletrônicos de Saúde , Computadores , Hospitais , Humanos
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