67 research outputs found

    Improving ductal carcinoma in situ classification by convolutional neural network with exponential linear unit and rank-based weighted pooling

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    Ductal carcinoma in situ (DCIS) is a pre-cancerous lesion in the ducts of the breast, and early diagnosis is crucial for optimal therapeutic intervention. Thermography imaging is a non-invasive imaging tool that can be utilized for detection of DCIS and although it has high accuracy (~88%), it is sensitivity can still be improved. Hence, we aimed to develop an automated artificial intelligence-based system for improved detection of DCIS in thermographs. This study proposed a novel artificial intelligence based system based on convolutional neural network (CNN) termed CNN-BDER on a multisource dataset containing 240 DCIS images and 240 healthy breast images. Based on CNN, batch normalization, dropout, exponential linear unit and rank-based weighted pooling were integrated, along with L-way data augmentation. Ten runs of tenfold cross validation were chosen to report the unbiased performances. Our proposed method achieved a sensitivity of 94.08±1.22%, a specificity of 93.58±1.49 and an accuracy of 93.83±0.96. The proposed method gives superior performance than eight state-of-theart approaches and manual diagnosis. The trained model could serve as a visual question answering system and improve diagnostic accuracy.British Heart Foundation Accelerator Award, UKRoyal Society International Exchanges Cost Share Award, UK RP202G0230Hope Foundation for Cancer Research, UK RM60G0680Medical Research Council Confidence in Concept Award, UK MC_PC_17171MINECO/FEDER, Spain/Europe RTI2018-098913-B100 A-TIC-080-UGR1

    Thermal Image Scanning for Influenza Border Screening: Results of an Airport Screening Study

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    Background: Infrared thermal image scanners (ITIS) appear an attractive option for the mass screening of travellers for influenza, but there are no published data on their performance in airports. Methods: ITIS was used to measure cutaneous temperature in 1275 airline travellers who had agreed to tympanic temperature measurement and respiratory sampling. The prediction by ITIS of tympanic temperature (37.8uC and 37.5uC) and of influenza infection was assessed using Receiver Operating Characteristic (ROC) curves and estimated sensitivity, specificity and positive predictive value (PPV). Findings: Using front of face ITIS for prediction of tympanic temperature 37.8uC,theareaundertheROCcurvewas0.86(9537.8uC, the area under the ROC curve was 0.86 (95%CI 0.75–0.97) and setting sensitivity at 86 % gave specificity of 71%. The PPV in this population of travellers, of whom 0.5 % were febrile using this definition, was 1.5%. We identified influenza virus infection in 30 travellers (3 Type A and 27 Type B). For ITIS prediction of influenza infection the area under the ROC curve was 0.66 (0.56–0.75), a sensitivity of 87% gave specificity of 39%, and PPV of 2.8%. None of the 30 influenza-positive travellers had tympanic temperature 37.8uC at screening (95%CI 0 % to 12%); three had no influenza symptoms. Conclusion: ITIS performed moderately well in detecting fever but in this study, during a seasonal epidemic of predominantly influenza type B, the proportion of influenza-infected travellers who were febrile was low and ITIS were no

    Differences in vocal characteristics between Cantonese and English produced by proficient Cantonese-English bilingual speakers - A long-term average spectral analysis

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    Objectives: The present study objectively examined the possible difference in vocal characteristics associated with English and Cantonese produced by proficient Cantonese-English bilingual speakers. Subjects and Methods: Forty native speakers of Cantonese (20 males and 20 females) who were proficient in Cantonese and English participated in the study. An array of acoustical parameters, including fundamental frequency (F0) values and first spectral peak (FSP), mean spectral energy (MSE), and spectral tilt (ST) extracted from long-term average speech spectra were obtained from connected speech samples produced in Cantonese and English by the bilingual speakers. Acoustical parameters were measured using Praat (P. Boersma & D. Weenink, Amsterdam, The Netherlands) and used to objectively describe the voice quality. Results: Results indicated that female bilingual speakers had significantly higher F0 values in speaking English than Cantonese. Although exhibiting comparable FSP values, the bilingual speakers showed significantly higher MSE and lower ST values when speaking Cantonese compared with English. Conclusions: The present findings imply that, even with the same phonatory apparatus, language being spoken can have an effect on the speakers' voice quality. © 2012 The Voice Foundation.link_to_subscribed_fulltex

    Mathematical modeling of skin bioheat transfer

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    Altered patterns of functional connectivity and causal connectivity in salience subnetwork of subjective cognitive decline and amnestic mild cognitive impairment

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    The subjective cognitive decline (SCD) may last for decades prior to the onset of dementia and has been proposed as a risk population for development to amnestic mild cognitive impairment (aMCI) and Alzheimer disease (AD). Disruptions of functional connectivity and causal connectivity (CC) in the salience network (SN) are generally perceived as prominent hallmarks of the preclinical AD. Nevertheless, the alterations in anterior SN (aSN), and posterior SN (pSN) remain unclear. Here, we hypothesized that both the functional connectivity (FC) and CC of the SN subnetworks, comprising aSN and pSN, were distinct disruptive in the SCD and aMCI. We utilized resting-state functional magnetic resonance imaging to investigate the altered FC and CC of the SN subnetworks in 28 healthy controls, 23 SCD subjects, and 29 aMCI subjects. In terms of altered patterns of FC in SN subnetworks, aSN connected to the whole brain was significantly increased in the left orbital superior frontal gyrus, left insula lobule, right caudate lobule, and left rolandic operculum gyrus (ROG), whereas decreased FC was found in the left cerebellum superior lobule and left middle temporal gyrus when compared with the HC group. Notably, no prominent statistical differences were obtained in pSN. For altered patterns of CC in SN subnetworks, compared to the HC group, the aberrant connections in aMCI group were separately involved in the right cerebellum inferior lobule (CIL), right supplementary motor area (SMA), and left ROG, whereas the SCD group exhibited more regions of aberrant connection, comprising the right superior parietal lobule, right CIL, left inferior parietal lobule, left post-central gyrus (PG), and right angular gyrus. Especially, SCD group showed increased CC in the right CIL and left PG, whereas the aMCI group showed decreased CC in the left pre-cuneus, corpus callosum, and right SMA when compared to the SCD group. Collectively, our results suggest that analyzing the altered FC and CC observed in SN subnetworks, served as impressible neuroimaging biomarkers, may supply novel insights for designing preclinical interventions in the preclinical stages of AD.Published versio
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