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

Due to the difficulties of the copying, vein identification has developed rapidly in recent years. The light source selection directly affects the image quality. This paper acquired by experiment the reflectivities of vein and non-vein irradiation with different wavelengths of near infra-red. Comparing the strength of reflectivities of various wave lengths, we found that there were the strongest contrasts between vein and non-vein in the 810 nm, and 810 nm near infra-red was suitable to a vein imaging light source. Finally, clear hand vein images were obtained with the selected light source.
Algorithms ; Biometry ; methods ; Hand ; anatomy & histology ; blood supply ; Humans ; Image Enhancement ; Image Processing, Computer-Assisted ; methods ; Infrared Rays ; Pattern Recognition, Automated ; Tomography, Optical ; methods ; Veins ; anatomy & histology

A fast and accurate intelligent identification is the developing trend of electrocardiogram (ECG) research. However, there are few methods by which satisfactory results could be obtained both in speed and in accuracy. A fast identification method of QRS wave was proposed based on moving window operation in this study. An 80 ms wide moving window was employed, in which simple difference and product operations were carried out with simple and less computation, and a very good inhibition of P and T waves and other noises was realized. Then the method was investigated with data from the MIT-BIH arrhythmia database with absence of digital filtering de-noising, and the identification accuracy of QRS complex reached 99.6%. The results showed that a rapid and accurate identification of QRS complex could be realized, which would meet the requirements for studying the real-time ECG monitoring equipment.
Algorithms ; Electrocardiography ; methods ; Humans ; Pattern Recognition, Automated ; Signal Processing, Computer-Assisted

To solve the ineffective problem of leukocytes classification based on multi-feature fusion in a single color space, we proposed an automatic leukocyte pattern recognition by means of feature fusion with color histogram and texture granular in multi-color space. The interactive performance of three color spaces (RGB, HSV and Lab), two features (color histogram and texture granular) and four similarity measured distance metrics (normalized intersection, Euclidean distance, chi2-metric distance and Mahalanobis distance) were discussed. The optimized classification modes of high precision, extensive universality and low cost to different leukocyte types were obtained respectively, and then the recognition system of tree-integration of the optimized modes was established. The experimental results proved that the performance of the fusion classification was improved by 12.3% at least.
Algorithms ; Clinical Laboratory Techniques ; Color ; Humans ; Image Enhancement ; methods ; Image Interpretation, Computer-Assisted ; methods ; Leukocyte Count ; methods ; Leukocytes ; classification ; cytology ; Pattern Recognition, Automated ; methods

This study was aimed to optimize the methods of magnetic resonance spectroscopy (MRS) to improve its quality in amygdala. Forty-three volunteers were examined at right and left amygdala using stimulated-echo acquisition mode (STEAM), and point-resolved spectroscopy series (PRESS) with and without saturation bands. The Cr-SNR, water-suppression level, water full width at half maximum (FWHM) and RMS noise of three sequences were compared. The results showed that (1) the Cr-SNR and water-suppression lelvel of PRESS with saturation bands were better than that of PRESS without saturation bands and STEAM (P<0.001); (2) the left and right RMS noise was significantly different both using PRESS with saturation bands and using STEAM (P<0.05); (3) there was a positive, significant correlation between Cr-SNR and voxel size (P<0.05). Therefore, PRESS with saturation bands is better than PRESS without saturation bands or STEAM for the spectroscopy of amygdala. It is also useful to make the voxel as big as possible to improve the spectral quality.
Adult ; Algorithms ; Amygdala ; metabolism ; physiology ; Artifacts ; Female ; Humans ; Magnetic Resonance Spectroscopy ; methods ; Male ; Pattern Recognition, Automated ; standards ; Young Adult

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

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