Underlying elements of image quality assessment: : Preference and terminology for communicating image quality characteristics

Image quality markedly affects the evaluation of images, and its control is crucial in studies using natural visual scenes as stimuli. Various image elements, such as sharpness or naturalness, can impact how observers view images and more directly how they evaluate their quality. To gain a better understanding of the types of interactions between these various elements, we conducted a study with a large set of images with multiple overlapping distortions, covering a wide range of quality variation. Observers assigned a quality rating on a 0-10 scale plus a verbal description of the images, explaining the elements on which their rating was based. Regression model predicting image quality ratings using 68 attributes uncovered the link between verbal descriptions and quality ratings and the importance of the image quality rating for each of the 68 image attributes. Brightness, naturalness, and good colors seem to be related to the highest image quality preference. However, the most important elements for predicting good image quality were related to image fidelity such as graininess and sharpness. This indicates that a certain level of image fidelity must be achieved before more subjective associations with, for instance, naturalness can emerge. Of the attributes, 72% had a negative impact on the preference judgment. This negative bias may be due to the fact that there are more ways that observers can perceive an image to fail than to excel when they are asked to evaluate image quality.Image quality markedly affects the evaluation of images, and its control is crucial in studies using natural visual scenes as stimuli. Various image elements, such as sharpness or naturalness, can impact how observers view images and, more directly, how they evaluate their quality. To gain a better understanding of the types of interactions between these various elements, we conducted a study with a large set of images with multiple overlapping distortions, covering a wide range of quality variation. Observers assigned a quality rating of the images on a 0–10 scale and gave a verbal description explaining the elements on which their rating was based. A regression model predicting image quality ratings using 68 attributes uncovered the link between verbal descriptions and quality ratings and the importance of the image quality rating for each of the 68 image attributes. Brightness, naturalness, and good colors seem to be related to the highest image quality preference. However, the most important elements for predicting good image quality were related to image fidelity such as graininess and sharpness. This indicates that a certain level of image fidelity must be achieved before more subjective associations with, for instance, naturalness can emerge. Of the attributes, 72% had a negative impact on the preference judgment. This negative bias may be due to the fact that there are more ways that observers can perceive an image to fail than to excel when they are asked to evaluate image quality.Peer reviewe

Upper Nasal Hemifield Location and Nonspatial Auditory Tones Accelerate Visual Detection during Dichoptic Viewing

Visual performance is asymmetric across the visual field, but locational biases that occur during dichoptic viewing are not well understood. In this study, we characterized horizontal, vertical and naso-temporal biases in visual target detection during dichoptic stimulation and explored whether the detection was facilitated by non-spatial auditory tones associated with the target's location. The detection time for single monocular targets that were suppressed from view with a 10 Hz dynamic noise mask presented to the other eye was measured at the 4 degrees intercardinal location of each eye with the breaking Continuous Flash Suppression (b-CFS) technique. Each target was either combined with a sound (i.e., high or low pitch tone) that was congruent or incongruent with its vertical location (i.e., upper or lower visual field) or presented without a sound. The results indicated faster detection of targets in the upper rather than lower visual field and faster detection of targets in the nasal than temporal hemifield of each eye. Sounds generally accelerated target detection, but the tone pitch-elevation congruency did not further enhance performance. These findings suggest that visual detection during dichoptic viewing differs from standard viewing conditions with respect to location-related perceptual biases and crossmodal modulation of visual perception. These differences should be carefully considered in experimental designs employing dichoptic stimulation techniques and in display applications that utilize dichoptic viewing.Peer reviewe

The role of outpatient visit after operative treatment of ankle fractures

It is a common practice that patients have a scheduled follow-up visit with radiographs following ankle fracture surgery. The aim of this study was to evaluate whether an early outpatient visit ( A change in treatment plan was observed in 9.8% of operatively treated ankle fracture patients. The mean age of the patients was 48 years and the mean follow-up time was 64 months. Of the changes in treatment plan, 91% were exclusively due to clinical findings such as infection. Only three of 878 patients required a change in their treatment plan based merely on the findings of the radiographs taken at the outpatient visit. Only 37% of the patients requiring a change in their postoperative management had solicited an unanticipated visit before the scheduled outpatient visit due to clinical problems such as infection or a cast-related issue. Our study showed that every tenth operatively treated ankle fracture patient requires a change in their treatment plan due to a clinical problem such as infection or a cast-related issue. Although at hospital discharge all patients are provided with written instructions on where to contact if problems related to the operated ankle emerge, only one third of the patients are aware of the clinically alarming symptoms and seek care when problems present. Our findings do not support obtaining routine radiographs at the early outpatient visit in an ankle fracture patient without clinical signs of a complication. (C) 2016 Published by Elsevier Ltd.Peer reviewe

Using machine learning for the personalised prediction of revision endoscopic sinus surgery

BackgroundRevision endoscopic sinus surgery (ESS) is often considered for chronic rhinosinusitis (CRS) if maximal conservative treatment and baseline ESS prove insufficient. Emerging research outlines the risk factors of revision ESS. However, accurately predicting revision ESS at the individual level remains uncertain. This study aims to examine the prediction accuracy of revision ESS and to identify the effects of risk factors at the individual level. MethodsWe collected demographic and clinical variables from the electronic health records of 767 surgical CRS patients >= 16 years of age. Revision ESS was performed on 111 (14.5%) patients. The prediction accuracy of revision ESS was examined by training and validating different machine learning models, while the effects of variables were analysed using the Shapley values and partial dependence plots. ResultsThe logistic regression, gradient boosting and random forest classifiers performed similarly in predicting revision ESS. Area under the receiving operating characteristic curve (AUROC) values were 0.744, 0.741 and 0.730, respectively, using data collected from the baseline visit until six months after baseline ESS. The length of time during which data were collected improved the prediction performance. For data collection times of 0, 3, 6 and 12 months after baseline ESS, AUROC values for the logistic regression were 0.682, 0.715, 0.744 and 0.784, respectively. The number of visits before or after baseline ESS, the number of days from the baseline visit to the baseline ESS, patient age, CRS with nasal polyps (CRSwNP), asthma, non-steroidal anti-inflammatory drug exacerbated respiratory disease and immunodeficiency or suspicion of it all associated with revision ESS. Patient age and number of visits before baseline ESS carried non-linear effects for predictions. ConclusionsIntelligent data analysis identified important predictors of revision ESS at the individual level, such as the frequency of clinical visits, patient age, Type 2 high diseases and immunodeficiency or a suspicion of it.Peer reviewe

Onko nilkkamurtuman leikkaushoidon jälkeinen kahden viikon kontrollikäynti tarpeen?

English abstrac

The relative proportion of comorbidities among rhinitis and rhinosinusitis patients and their impact on visit burden

Background The aim was to evaluate the relative proportion of Non-steroidal anti-inflammatory drug exacerbated respiratory disease (NERD) and other comorbidities, and their impact on the burden of outpatient visits due to allergic rhinitis (AR), non-allergic rhinitis (NAR), acute rhinosinusitis (ARS), and chronic rhinosinusitis with nasal polyps (CRSwNP) and without (CRSsNP). Methods We used hospital registry data of a random sample of 5080 rhinitis/rhinosinusitis patients diagnosed during 2005-2019. International Statistical Classification of Diseases and Related Health Problems (ICD10) diagnoses, visits, and other factors were collected from electronic health records by using information extraction and data processing methods. Cox's proportional hazards model was used for modeling the time to the next outpatient visit. Results The mean (+/- standard deviation) age of the population was 33.6 (+/- 20.7) years and 56.1% were female. The relative proportion of AR, NAR, ARS, CRSsNP and CRSwNP, were 33.5%, 27.5%, 27.2%, 20.7%, and 10.9%, respectively. The most common other comorbidities were asthma (44.4%), other chronic respiratory diseases (38.5%), musculoskeletal diseases (38.4%), and cardiovascular diseases (35.7%). Non-steroidal anti-inflammatory drug exacerbated respiratory disease existed in 3.9% of all patients, and 17.7% of the CRSwNP group. The relative proportion of subjects having 1, 2, 3 and >= 4 other diseases were 18.0%, 17.6%, 17.0%, 37.0%, respectively. All diseases except AR, ARS, and mouth breathing, were associated with a high frequency of outpatient visits. Conclusions Our results revealed a high relative proportion of NERD and other comorbidities, which affect the burden of outpatient visits and hence confirm the socioeconomic impact of upper airway diseases.Peer reviewe

Validation of the Lean Healthcare Implementation Self-Assessment Instrument (LHISI) in the finnish healthcare context

Lean management is growing in popularity in the healthcare sector worldwide, yet healthcare organizations are struggling with assessing the maturity of their Lean implementation and monitoring its change over time. Most existing methods for such assessments are time consuming, require site visits by external consultants, and lack frontline involvement. The original Lean Healthcare Implementation Self-Assessment Instrument (LHISI) was developed by the Center for Lean Engagement and Research (CLEAR), University of California, Berkeley as a Lean principles-based survey instrument that avoids the above problems. We validated the original LHISI in the context of Finnish healthcare.Background Lean management is growing in popularity in the healthcare sector worldwide, yet healthcare organizations are struggling with assessing the maturity of their Lean implementation and monitoring its change over time. Most existing methods for such assessments are time consuming, require site visits by external consultants, and lack frontline involvement. The original Lean Healthcare Implementation Self-Assessment Instrument (LHISI) was developed by the Center for Lean Engagement and Research (CLEAR), University of California, Berkeley as a Lean principles-based survey instrument that avoids the above problems. We validated the original LHISI in the context of Finnish healthcare. Methods The original HISI survey was sent over a secure organizational email system to the over 26,000 employees of the Hospital District of Helsinki and Uusimaa in March 2020. The data were randomly split with one part used to carry out an exploratory factor analysis (EFA), and the other for testing the resulting model using confirmatory factor analysis (CFA). Results A total of 6073 employees responded to the LHISI survey, for an overall response rate of 23%. The results indicated that the 43 items used in the original LHISI can be reduced to 25 items, and these items measure a five-dimensional model of the progress of Lean implementation: leadership, commitment, standard work, communication, and daily management system. In comparison with a single-factor model, the fit measures for the 5-factor model were better: smaller X-2, larger comparative fit index (CFI), smaller root mean square error of approximation (RMSEA), and smaller standardized root mean square residual (SRMR). Conclusions The 25 item LHISI is valid and feasible to use in the context of Finnish healthcare. The LHISI allows the organization to self-monitor the progress of its Lean implementation and provides the leadership with actionable knowledge to guide the path towards Lean maturity across the organization. Our findings encourage further studies on the adoption and validation of the LHISI in healthcare organizations worldwide.Peer reviewe

Diabetes : Käypä hoito -suosituksen päivitystiivistelmä

English summar

Impact of Machine Learning Assistance on the Quality of Life Prediction for Breast Cancer Patients

Proper and well-timed interventions may improve breast cancer patient adaptation, resilience and quality of life (QoL) during treatment process and time after disease. The challenge is to identify those patients who would benefit most from a particular intervention. The aim of this study was to measure whether the machine learning prediction incorporated in the clinical decision support system (CDSS) improves clinicians' performance to predict patients' QoL during treatment process. We conducted an experimental setup in which six clinicians used CDSS and predicted QoL for 60 breast cancer patients. Each patient was evaluated both with and without the aid of machine learning prediction. The clinicians were also open-ended interviewed to investigate the usage and perceived benefits of CDSS with the machine learning prediction aid. Clinicians' performance to evaluate the patients' QoL was higher with the aid of machine learning predictions than without the aid. AUROC of clinicians was .777 (95% CI .691 - .857) with the aid and .755 (95% CI .664 - .840) without the aid. When the machine learning model's prediction was correct, the average accuracy (ACC) of the clinicians was .788 (95% CI .739 - .838) with the aid and .717 (95% CI .636 - .798) without the aid.Peer reviewe

A nationwide real-world study on dynamic ustekinumab dosing and concomitant medication use among Crohn's disease patients in Finland

Background Real-world evidence to support optimal ustekinumab dosing for refractory Crohn's disease (CD) patients remains limited. Data from a retrospective nationwide chart review study was utilized to explore ustekinumab dosing dynamics and optimization, identify possible clinical predictors of dose intensification, and to evaluate ustekinumab trough concentrations (TCs) and concomitant medication use in Finland. Methods Information gathered from17 Finnish hospitals included clinical chart data from 155 adult CD patients who received intravenous ustekinumab induction during 2017-2018. Data on ustekinumab dosing and TCs, concomitant corticosteroid and immunosuppressant use, and antiustekinumab antibodies were analyzed in a two-year follow-up, subject to availability. Results Among 140 patients onustekinumab maintenance therapy, dose optimization was required in 55(39%) of the patients, and 41/47 dose-intensified patients (87%) persisted on ustekinumab. At baseline, dose-intensified patient group had significantly higher C-reactive protein (CRP) levels, and at week 16, significantly lower ustekinumab TCs than in patients without dose intensification. Irrespective of dose optimization, a statistically significant reduction in the use of corticosteroids was observed at both 16 weeks and one year, coupled with an increased proportion of patients on ustekinumab monotherapy. Antiustekinumab antibodies were undetectable in all 28 samples from 25 patients collected throughout the study period. Conclusions Nearly a third of all CD patients on ustekinumab maintenance therapy, with a history of treatment-refractory and long-standing disease, required dose intensification. These patients persisted on ustekinumab and had significant reduction of corticosteroid use. Increased baseline CRP was identified as the sole indicator of dose intensification.Peer reviewe