16 research outputs found

    A METHOD OF EXTRACTING AND EVALUATING GOOD AND BAD REPUTATIONS FOR NATURAL LANGUAGE EXPRESSIONS

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    Although a users' opinion or a live voice is a very useful information for text mining of the business, it is difficult to extract good and bad reputations of users from texts written in natural language. The good and bad reputations discussed here depend on users' claims, interests and demands. This paper presents a method of determining these reputations in commodity review sentences. Multi-attribute rule is introduced to extract the reputations from sentences, and four-stage-rules are defined in order to evaluate good and bad reputations step by step. A deterministic multi-attribute pattern matching algorithm is utilized to determine the reputations efficiently.From simulation results for 2,240 review comments, it is verified that the multi-attribute pattern matching algorithm is 63.1 times faster than the Aho and Corasick method. The precision and recall of extracted reputations for each commodity are 94% and 93% respectively. Moreover, the precision and recall of the resulting reputations for each rule are 95% and 95% respectively.Good and bad reputations, text mining, natural language understanding, multi-attribute rules, deterministic multi-attribute pattern-matching

    Clinical Factors Associated with Lamina Cribrosa Thickness in Patients with Glaucoma, as Measured with Swept Source Optical Coherence Tomography.

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    PURPOSE:To investigate the influence of various risk factors on thinning of the lamina cribrosa (LC), as measured with swept-source optical coherence tomography (SS-OCT; Topcon). METHODS:This retrospective study comprised 150 eyes of 150 patients: 22 normal subjects, 28 preperimetric glaucoma (PPG) patients, and 100 open-angle glaucoma patients. Average LC thickness was determined in a 3 x 3 mm cube scan of the optic disc, over which a 4 x 4 grid of 16 points was superimposed (interpoint distance: 175 μm), centered on the circular Bruch's membrane opening. The borders of the LC were defined as the visible limits of the LC pores. The correlation of LC thickness with Humphrey field analyzer-measured mean deviation (MD; SITA standard 24-2), circumpapillary retinal nerve fiber layer thickness (cpRNFLT), the vertical cup-to-disc (C/D) ratio, and tissue mean blur rate (MBR) was determined with Spearman's rank correlation coefficient. The relationship of LC thickness with age, axial length, intraocular pressure (IOP), MD, the vertical C/D ratio, central corneal thickness (CCT), and tissue MBR was determined with multiple regression analysis. Average LC thickness and the correlation between LC thickness and MD were compared in patients with the glaucomatous enlargement (GE) optic disc type and those with non-GE disc types, as classified with Nicolela's method. RESULTS:We found that average LC thickness in the 16 grid points was significantly associated with overall LC thickness (r = 0.77, P < 0.001). The measurement time for this area was 12.4 ± 2.4 minutes. Average LC thickness in this area had a correlation coefficient of 0.57 with cpRNFLT (P < 0.001) and 0.46 (P < 0.001) with MD. Average LC thickness differed significantly between the groups (normal: 268 ± 23 μm, PPG: 248 ± 13 μm, OAG: 233 ± 20 μm). Multiple regression analysis showed that MD (β = 0.29, P = 0.013), vertical C/D ratio (β = -0.25, P = 0.020) and tissue MBR (β = 0.20, P = 0.034) were independent variables significantly affecting LC thickness, but age, axial length, IOP, and CCT were not. LC thickness was significantly lower in the GE patients (233.9 ± 17.3 μm) than the non-GE patients (243.6 ± 19.5 μm, P = 0.040). The correlation coefficient between MD and LC thickness was 0.58 (P < 0.001) in the GE patients and 0.39 (P = 0.013) in the non-GE patients. CONCLUSION:Cupping formation and tissue blood flow were independently correlated to LC thinning. Glaucoma patients with the GE disc type, who predominantly have large cupping, had lower LC thickness even with similar glaucoma severity

    Quality Assessment of Endoscopic Forceps Biopsy Samples under Magnifying Narrow Band Imaging for Histological Diagnosis of Cervical Intraepithelial Neoplasia: A Feasibility Study

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    The current standard for diagnosing cervical intraepithelial neoplasia (CIN) is colposcopy followed by punch biopsy. We have developed flexible magnifying endoscopy with narrow band imaging (ME-NBI) for the diagnosis of CIN. Here, we investigated the feasibility of targeted endoscopic forceps biopsy (E-Bx) under guidance of ME-NBI for the diagnosis of CIN. We prospectively enrolled 32 consecutive patients with confirmed or suspected high-grade CIN undergoing cervical conization. Next to colposcopy, the same patients underwent ME-NBI just before conization. ME-NBI was performed, and 30 E-Bx samples were taken from lesions suspicious for high-grade CIN and 15 from non-suspicious mucosa. We recalled 82 punch biopsy (P-Bx) specimens taken from lesions suspicious for high-grade CIN under colposcopic examination before enrollment. The proportion of sufficient biopsy samples, which had an entire mucosal layer with subepithelial tissue, for the diagnosis of CIN was evaluated by both methods. Performance of targeted E-Bx for the final diagnosis of at least high-grade CIN was calculated. Seventeen P-Bx specimens were unavailable. The proportion of sufficient samples with E-Bx was 84%, which was similar to that with P-Bx (87%) (p = 0.672). The sensitivity, specificity, and accuracy of ME-NBI using E-Bx was 92%, 81%, and 88%, respectively. In conclusion, ME-NBI-guided E-Bx samples were feasible for histological diagnoses of CIN, and further investigation of its diagnostic accuracy is warranted

    AvgLCT measurements made with the simplified version of the software.

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    <p>(A) Bar graph indicating LC thickness in patients with different stages of glaucoma (normal: n = 22, PPG: n = 28, OAG: n = 100). Note: there were significant differences between these groups (Kruskal-Wallis test followed by Steel-Dwass test). *: <i>P</i> < 0.01. (B) ROC curve. The area under the ROC curve was 0.91, with a cutoff value of 246.3 μm.</p

    Simplified software technique for measuring lamina cribrosa (LC) thickness in a 4 x 4 grid.

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    <p>(A) 4 x 4 grid superimposed on an en-face image of the LC, showing the position of the B-scan images below. (B-E) Horizontal cross-sectional B-scan images, with orange dots indicating the anterior and posterior borders of the LC. Average LC thickness was defined as the average thickness in the 16 grid cells.</p
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