OBJECTIVES: Clinical discharge summaries provide valuable information about patients' clinical history, which is helpful for the realization of intelligent healthcare applications. The documents tend to take the form of separate segments based on temporal or topical information. If a patient's clinical history can be seen as a consecutive sequence of clinical events, then each temporal segment can be seen as a snapshot, providing a certain clinical context at a specific moment. This study aimed to demonstrate a temporal segmentation method of Korean clinical narratives for identifying textual snapshots of patient history as a proof-of-a-concept. METHODS: Our method uses pattern-based segmentation to approximate human recognition of the temporal or topical shifts in clinical documents. We utilized rheumatic patients' discharge summaries and transformed them into sequences of constituent chunks. We built 97 single pattern functions to denote whether a certain chunk has attributes that indicate that it can be a segment boundary. We manually defined the relationships between the pattern functions to resolve multiple pattern matchings and to make a final decision. RESULTS: The algorithm segmented 30 discharge summaries and processed 1,849 decision points. Three human judges were asked whether they agreed with the algorithm's prediction, and the agreement percentage on the judges' majority opinion was 89.61%. CONCLUSIONS: Although this method is based on manually constructed rules, our findings demonstrate that the proposed algorithm can achieve fairly good segmentation results, and it may be the basis for methodological improvement in the future.
Delivery of Health Care ; Electronic Health Records ; Humans ; Methods ; Natural Language Processing ; Pattern Recognition, Automated ; Rheumatic Diseases

Breast cancer is the second leading cancer for Korean women and its incidence rate has been increasing annually. If early diagnosis were implemented with epidemiologic data, the women could easily assess breast cancer risk using internet. National Cancer Institute in the United States has released a Web-based Breast Cancer Risk Assessment Tool based on Gail model. However, it is inapplicable directly to Korean women since breast cancer risk is dependent on race. Also, it shows low accuracy (58%-59%). In this study, breast cancer discrimination models for Korean women are developed using only epidemiological case-control data (n = 4,574). The models are configured by different classification techniques: support vector machine, artificial neural network, and Bayesian network. A 1,000-time repeated random sub-sampling validation is performed for diverse parameter conditions, respectively. The performance is evaluated and compared as an area under the receiver operating characteristic curve (AUC). According to age group and classification techniques, AUC, accuracy, sensitivity, specificity, and calculation time of all models were calculated and compared. Although the support vector machine took the longest calculation time, the highest classification performance has been achieved in the case of women older than 50 yr (AUC = 64%). The proposed model is dependent on demographic characteristics, reproductive factors, and lifestyle habits without using any clinical or genetic test. It is expected that the model could be implemented as a web-based discrimination tool for breast cancer. This tool can encourage potential breast cancer prone women to go the hospital for diagnostic tests.
Adult ; Aged ; Aged, 80 and over ; Breast Neoplasms/*diagnosis/*epidemiology ; Diagnosis, Computer-Assisted/*methods ; Early Detection of Cancer/*methods ; Female ; Humans ; *Machine Learning ; Middle Aged ; Pattern Recognition, Automated/methods ; Prevalence ; Reproducibility of Results ; Republic of Korea/epidemiology ; Risk Assessment/methods ; Risk Factors ; Sensitivity and Specificity ; Women's Health/*statistics & numerical data

Facial paralysis is a frequently-occurring disease, which causes the loss of the voluntary muscles on one side of the face due to the damages the facial nerve and results in an inability to close the eye and leads to dropping of the angle of the mouth. There have been few objective methods to quantitatively diagnose it and assess this disease for clinically treating the patients so far. The skin temperature distribution of a healthy human body exhibits a contralateral symmetry. Facial paralysis usually causes an alteration of the temperature distribution of body with the disease. This paper presents the use of the histogram distance of bilateral local binary pattern (LBP) in the facial infrared thermography to measure the asymmetry degree of facial temperature distribution for objective assessing the severity of facial paralysis. Using this new method, we performed a controlled trial to assess the facial nerve function of the healthy subjects and the patients with Bell's palsy respectively. The results showed that the mean sensitivity and specificity of this method are 0.86 and 0.89 respectively. The correlation coefficient between the asymmetry degree of facial temperature distribution and the severity of facial paralysis is an average of 0.657. Therefore, the histogram distance of local binary pattern in the facial infrared thermography is an efficient clinical indicator with respect to the diagnosis and assessment of facial paralysis.
Facial Paralysis ; diagnosis ; physiopathology ; Humans ; Infrared Rays ; Pattern Recognition, Automated ; methods ; Skin Temperature ; Thermography ; instrumentation

Discriminative common vector (DCV) is an effective method that was proposed for the small sample size problems of face recognition. There is the same problem in brain-computer interface (BCI). Using directly the linear discriminative analysis (LDA) could result in errors because of the singularity of the within-class matrix of data. In our studies, we used the DCV method from the common vector theory in the within-class scatter matrix of data of all classes, and then applied eigenvalue decomposition to the common vectors to obtain the final projected vectors. Then we used kernel discriminative common vector (KDCV) with different kernel. Three data sets that include BCI Competition I data set, Competition II data set IV, and a data set collected by ourselves were used in the experiments. The experiment results of 93%, 77% and 97% showed that this feature extraction method could be used well in the classification of imagine data in BCI.
Algorithms ; Artificial Intelligence ; Brain-Computer Interfaces ; Discriminant Analysis ; Electroencephalography ; Face ; anatomy & histology ; Humans ; Pattern Recognition, Automated ; methods ; Principal Component Analysis ; Sample Size ; Signal Processing, Computer-Assisted ; User-Computer Interface

The metabolomic analysis of three Cimicifuga species was performed using H-NMR spectroscopy and pattern recognition (PR) techniques. A broad range of metabolites could be detected by 'H-NMR spectroscopy without any chromatographic separation. The analysis using principal component analysis (PCA) and discriminant partial least square (DPLS) of the 1H-NMR spectrum showed a clear discrimination between C. foetida and the other two species. The major metabolites responsible for the discrimination were triterpenoid saponins and saccharides. These results indicated that the combination of 1H-NMR and PR provides a useful tool for chemotaxonomic analysis and authentification of Cimicifuga species, and could used for the quality control of plant materials.
Cimicifuga ; classification ; Discriminant Analysis ; Drugs, Chinese Herbal ; classification ; standards ; Magnetic Resonance Spectroscopy ; methods ; Metabolomics ; methods ; Pattern Recognition, Automated ; Principal Component Analysis ; Protons ; Saponins ; isolation & purification ; Triterpenes ; isolation & purification

To improve accuracy of estimation in planted safflower acreage,we selected agricultural area in Yumin County, Xinjiang as the study area. There safflower was concentrated planted. Supervised classification based on Principal Component Analysis (PCA) and texture feature were used to obtain the safflower acreage from image captured by ZY-3. The classification result was compared with only spectral feature and spectral feature with texture feature. The research result shows that this method can effectively solve the problem of low accuracy and fracture classification result in single data source classification. The overall accuracy is 87.519 1%, which increases by 7.117 2% compared with single data source classification. Therefore, the classification method based on PCA and texture features can be adapted to RS image classification and estimate the acreage of safflower. This study provides a feasible solution for estimation of planted safflower acreage by image captured by ZY-3 satellite.
Algorithms ; Carthamus tinctorius ; chemistry ; growth & development ; Image Processing, Computer-Assisted ; Pattern Recognition, Automated ; Principal Component Analysis ; methods ; Remote Sensing Technology ; methods

OBJECTIVE: We aimed to evaluate the time efficiency and diagnostic accuracy of automated myocardial computed tomography perfusion (CTP) image analysis software. MATERIALS AND METHODS: 320-row CTP was performed in 30 patients, and analyses were conducted independently by three different blinded readers by the use of two recent software releases (version 4.6 and novel version 4.71GR001, Toshiba, Tokyo, Japan). Analysis times were compared, and automated epi- and endocardial contour detection was subjectively rated in five categories (excellent, good, fair, poor and very poor). As semi-quantitative perfusion parameters, myocardial attenuation and transmural perfusion ratio (TPR) were calculated for each myocardial segment and agreement was tested by using the intraclass correlation coefficient (ICC). Conventional coronary angiography served as reference standard. RESULTS: The analysis time was significantly reduced with the novel automated software version as compared with the former release (Reader 1: 43:08 +/- 11:39 min vs. 09:47 +/- 04:51 min, Reader 2: 42:07 +/- 06:44 min vs. 09:42 +/- 02:50 min and Reader 3: 21:38 +/- 3:44 min vs. 07:34 +/- 02:12 min; p < 0.001 for all). Epi- and endocardial contour detection for the novel software was rated to be significantly better (p < 0.001) than with the former software. ICCs demonstrated strong agreement (> or = 0.75) for myocardial attenuation in 93% and for TPR in 82%. Diagnostic accuracy for the two software versions was not significantly different (p = 0.169) as compared with conventional coronary angiography. CONCLUSION: The novel automated CTP analysis software offers enhanced time efficiency with an improvement by a factor of about four, while maintaining diagnostic accuracy.
Aged ; Analysis of Variance ; Body Mass Index ; Coronary Angiography ; Coronary Artery Disease/*radiography ; *Efficiency, Organizational ; Female ; Humans ; Male ; Middle Aged ; Myocardial Perfusion Imaging/*methods ; Pattern Recognition, Automated/*methods ; Prospective Studies ; Radiographic Image Interpretation, Computer-Assisted/*methods ; *Software ; Statistics, Nonparametric ; Time Factors ; Tomography, X-Ray Computed/*methods

This paper is aimed to fulfill a prototype system used to classify and retrieve retinal image automatically. With the content-based image retrieval (CBIR) technology, a method to represent the retinal characteristics mixing the fundus image color (gray) histogram with bright, dark region features and other local comprehensive information was proposed. The method uses kernel principal component analysis (KPCA) to further extract nonlinear features and dimensionality reduced. It also puts forward a measurement method using support vector machine (SVM) on KPCA weighted distance in similarity measure aspect. Testing 300 samples with this prototype system randomly, we obtained the total image number of wrong retrieved 32, and the retrieval rate 89.33%. It showed that the identification rate of the system for retinal image was high.
Algorithms ; Fundus Oculi ; Humans ; Image Processing, Computer-Assisted ; methods ; Information Storage and Retrieval ; methods ; Numerical Analysis, Computer-Assisted ; Ophthalmoscopy ; standards ; Pattern Recognition, Automated ; methods ; Retina ; pathology ; Retinal Vessels ; pathology

This paper presents an automatic calculation method for angiography image, which enables programs to intellectively acquire several parameters of blood vessels, such as contours, segments, widths, etc. and then intellectively identify the angiostenosis parts. This method is a kind of automatic optic inspection (AOI) technology. Blood vessels usually distribute as curves and have a fastening direction. According to this feature, the approach performs inspection automatically using improved Steger algorithm, which firstly computes the convolution between image and Gaussian function kernel, and then computes second order Taylor expansion at eac pixel. And further the eigenvalues and eigenvectors of Hessian matrix are calculated on each pixel to obtain the direction of lines and local maximum of second derivative at that point. Hysteresis threshold and directional connection operators are then used to generate blood vessel skeleton. Finally we can compute the blood vessel widths for every sub-pixel object points on blood vessel curve. For given digital X-ray images of hearts with blood vessel local straitness, experiments showed that this method had the ability of getting all the data we need and could find the local confined parts in blood vessels. This approach is proved to have a good effort for angiography images, and it has some advantages such as fast speed, high accuracy, good robustness and no need for human interventions. It could also be a promising computer aided diagnosis method.
Algorithms ; Angiography ; instrumentation ; methods ; Artifacts ; Blood Vessels ; pathology ; Constriction, Pathologic ; diagnostic imaging ; Contrast Media ; Humans ; Pattern Recognition, Automated ; methods ; Radiographic Image Interpretation, Computer-Assisted ; methods

The control of prosthetic hand is always a focus in prosthesis research. For solving current problems of controlling signals of skin surface electrical signals, we applied force myography (FMG) signals in prosthetic control of this system. The control system based on FMG signals were designed, containing signal acquisition and pre-processing, prosthetic control, motor driving and so on. Two-freedom artificial hand with proportional control was proposed through acquiring two-channel FMG signals from the amputee stump. The proportional control of prosthetic hand was achieved according to the average of FMG amplitude. The results showed that the control system had a great potential to control artificial hand and to realize speed adjustment effectively. Besides, the Virtual instrument software LabVIEW is adopted to establish the FMG signal collection and calibration of experiment system.
Algorithms ; Artificial Limbs ; Electromyography ; instrumentation ; methods ; Hand ; physiology ; Humans ; Movement ; physiology ; Myography ; Pattern Recognition, Automated ; methods ; Prosthesis Design