Detection of microcalcifications in mammograms using error of prediction and statistical measures

A two-stage method for detecting microcalcifications in mammograms is presented. In the first stage, the determination of the candidates for microcalcifications is performed. For this purpose, a 2-D linear prediction error filter is applied, and for those pixels where the prediction error is larger than a threshold, a statistical measure is calculated to determine whether they are candidates for microcalcifications or not. In the second stage, a feature vector is derived for each candidate, and after a classification step using a support vector machine, the final detection is performed. The algorithm is tested with 40 mammographic images, from Screen Test: The Alberta Program for the Early Detection of Breast Cancer with 50- m resolution, and the results are evaluated using a freeresponse receiver operating characteristics curve. Two different analyses are performed: an individual microcalcification detection analysis and a cluster analysis. In the analysis of individual microcalcifications, detection sensitivity values of 0.75 and 0.81 are obtained at 2.6 and 6.2 false positives per image, on the average, respectively. The best performance is characterized by a sensitivity of 0.89, a specificity of 0.99, and a positive predictive value of 0.79. In cluster analysis, a sensitivity value of 0.97 is obtained at 1.77 false positives per image, and a value of 0.90 is achieved at 0.94 false positive per imag

Comparison of bioinspired algorithms applied to cancer database

Cancer is not just a disease; it is a set of diseases. Breast cancer is the second most common cancer worldwide after lung cancer, and it represents the most frequent cause of cancer death in women (Thurtle et al. in: PLoS Med 16(3):e1002758, 2019, 1]). If it is diagnosed at an early age, the chances of survival are greater. The objective of this research is to compare the performance of method predictions: (i) Logistic Regression, (ii) K-Nearest Neighbor, (iii) K-means, (iv) Random Forest, (v) Support Vector Machine, (vi) Linear Discriminant Analysis, (vii) Gaussian Naive Bayes, and (viii) Multilayer Perceptron within a cancer database

Visual fixation in the intensive care unit: a strong predictor of post-traumatic amnesia and long-term recovery after moderate-to-severe traumatic brain injury

Objective: We examined whether visual fixation at 24h of intensive care unit (ICU) admission is superior to the initial Glasgow Coma Scale (GCS) score to predict PTA duration and long-term TBI recovery. Design: Two-phase cohort study. Setting: Level I trauma ICU. Patients: Moderate-to-severe TBI discharged alive between 2010-2013. Interventions: None. Measurements and Main Results: Presence/absence of visual fixation at 24h of ICU-admission was determined through standard behavioral assessments in 181 TBI patients and compared to the GCS score to predict PTA duration during hospitalization (Phase 1) and performance on the Glasgow Outcome Scale-Extended (GOS-E) 10-40 months after (n=144; Phase 2a). A subgroup also completed a visual attention task (n=35; Phase 2b) and brain magnetic resonance imaging post-TBI (n=23; Phase 2c). Presence/absence of visual fixation at 24h of ICU-admission showed a sensitivity of 84%, a specificity of 82% and an AUC of 0.87 for the prediction of PTA duration. Visual fixation (AUC=0.85) was also found as performant as PTA (AUC=0.81; difference-between-AUC=0.04; 95%CI:-0.03-0.116; p=0.28) for the prediction of GOS-E scores. Conversely, the GCS score was a poor predictor of both PTA and GOS-E. Even when controlling for age/medication/CT scan findings, fixation remained a significant predictor of GOS-E scores (=-0.29, p<0.05). Poorer attention performance and increased regional brain volume deficits were also observed in participants who could not fixate 24h following ICU-admission versus those who could. Conclusions: Visual fixation within 24h of ICU-admission could be as performant as PTA for predicting TBI recovery, introducing a new variable of interest in TBI outcome research

Prediction of early unplanned intensive care unit readmission in a UK tertiary-care hospital: A cross-sectional machine learning approach

Objectives: Unplanned readmissions to the intensive care unit (ICU) are highly undesirable, increasing variance in care, making resource planning difficult, and potentially increasing length of stay and mortality in some settings. Identifying patients who are likely to suffer unplanned ICU readmission could reduce the frequency of this adverse event. Setting: A single academic, tertiary care hospital in the United Kingdom. Participants: A set of 3,326 ICU episodes collected between October 2014 and August 2016. All records were of patients who visited an ICU at some point during their stay. We excluded patients who: were ≤ 16 years of age; visited intensive care units other than the general and neurosciences ICU; were missing crucial electronic patient record measurements; or had indeterminate ICU discharge outcomes or very early or extremely late discharge times. After exclusion, 2,018 outcome-labeled episodes remained. Primary and Secondary Outcome Measures: Area under the receiver operating characteristic curve (AUROC) for prediction of unplanned ICU readmission or in-hospital death within 48 hours of first ICU discharge. Results: In ten-fold cross-validation, an ensemble predictor was trained on data from both the target hospital and the MIMIC-III database and tested on the target hospital’s data. This predictor discriminated between patients with the unplanned ICU readmission or death outcome and those without this outcome, attaining mean AUROC of 0.7095 (SE 0.0260), superior to the purpose-built SWIFT score (AUROC = 0.6082, SE 0.0249; p = 0.014, pairwise t-test). Conclusions: Despite the inherent difficulties, we demonstrate that a novel ML algorithm based on transfer learning could achieve good discrimination, over and above that of the treating clinicians or the value added by the SWIFT score. Accurate prediction of unplanned readmission could be used to target resources more efficiently.esearch reported in this publication was supported by the National Institute of Nursing Research, of the National Institutes of Health, under award number R43NR015945

Detection of microcalcifications in mammograms using error of prediction and statistical measures

A two-stage method for detecting microcalcifications in mammograms is presented. In the first stage, the determination of the candidates for microcalcifications is performed. For this purpose, a 2-D linear prediction error filter is applied, and for those pixels where the prediction error is larger than a threshold, a statistical measure is calculated to determine whether they are candidates for microcalcifications or not. In the second stage, a feature vector is derived for each candidate, and after a classification step using a support vector machine, the final detection is performed. The algorithm is tested with 40 mammographic images, from Screen Test: The Alberta Program for the Early Detection of Breast Cancer with 50- m resolution, and the results are evaluated using a freeresponse receiver operating characteristics curve. Two different analyses are performed: an individual microcalcification detection analysis and a cluster analysis. In the analysis of individual microcalcifications, detection sensitivity values of 0.75 and 0.81 are obtained at 2.6 and 6.2 false positives per image, on the average, respectively. The best performance is characterized by a sensitivity of 0.89, a specificity of 0.99, and a positive predictive value of 0.79. In cluster analysis, a sensitivity value of 0.97 is obtained at 1.77 false positives per image, and a value of 0.90 is achieved at 0.94 false positive per imageMinisterio de Sanidad FIS05-202

Urethral catheters: can we reduce use?

<p>Abstract</p> <p>Background</p> <p>Indwelling urinary catheters are the main cause of healthcare-associated urinary tract infections. It can be expected that reduction of the use of urinary catheters will lead to decreased numbers of urinary tract infection.</p> <p>Methods</p> <p>The efficacy of an intervention programme to improve adherence to recommendations to reduce the use of urethral catheters was studied in a before-after comparison in ten Dutch hospitals. The programme detected barriers and facilitators and each individual facility was supported with developing their own intervention strategy. Outcome was evaluated by the prevalence of catheters, alternatives such as diapers, numbers of urinary tract infections, the percentage of correct indications and the duration of catheterization. The costs of the implementation as well as the catheterization were evaluated.</p> <p>Results</p> <p>Of a population of 16,495 hospitalized patients 3335 patients of whom 2943 were evaluable for the study, had a urethral catheter. The prevalence of urethral catheters decreased insignificantly in neurology (OR 0.93; 95% CI 0.77 - 1.13) and internal medicine wards (OR 0.97; 95% CI 0.83 - 1.13), decreased significantly in surgical wards (OR 0.84; 95% CI 0.75 - 0.96), but increased significantly in intensive care (IC) and coronary care (CC) units (OR 1.48; 95% CI 1.01 - 2.17). The use of alternatives was limited and remained so after the intervention. Duration of catheterization decreased insignificantly in IC/CC units (ratio after/before 0.95; 95% CI 0.78 - 1.16) and neurology (ratio 0.97; 95% CI 0.80 - 1.18) and significantly in internal medicine (ratio 0.81; 95% CI 0.69 - 0.96) and surgery wards (ratio 0.80; 95% CI 0.71 - 0.90). The percentage of correct indications on the day of inclusion increased from 50 to 67% (p < 0.0001). The prevalence of urinary tract infections in catheterized patients did not change. The mean cost saved per 100 patients was € 537.</p> <p>Conclusion</p> <p>Targeted implementation of recommendations from an existing guideline can lead to better adherence and cost savings. Especially, hospitals which use a lot of urethral catheters or where catheterization is prolonged, can expect important improvements.</p

Management of patients with biliary sphincter of Oddi disorder without sphincter of Oddi manometry

<p>Abstract</p> <p>Background</p> <p>The paucity of controlled data for the treatment of most biliary sphincter of Oddi disorder (SOD) types and the incomplete response to therapy seen in clinical practice and several trials has generated controversy as to the best course of management of these patients. In this observational study we aimed to assess the outcome of patients with biliary SOD managed without sphincter of Oddi manometry.</p> <p>Methods</p> <p>Fifty-nine patients with biliary SOD (14% type I, 51% type II, 35% type III) were prospectively enrolled. All patients with a dilated common bile duct were offered endoscopic retrograde cholangiopancreatography (ERCP) and sphincterotomy whereas all others were offered medical treatment alone. Patients were followed up for a median of 15 months and were assessed clinically for response to treatment.</p> <p>Results</p> <p>At follow-up 15.3% of patients reported complete symptom resolution, 59.3% improvement, 22% unchanged symptoms, and 3.4% deterioration. Fifty-one percent experienced symptom resolution/improvement on medical treatment only, 12% after sphincterotomy, and 10% after both medical treatment/sphincterotomy. Twenty percent experienced at least one recurrence of symptoms after initial response to medical and/or endoscopic treatment. Fifty ERCP procedures were performed in 24 patients with an 18% complication rate (16% post-ERCP pancreatitis). The majority of complications occurred in the first ERCP these patients had. Most complications were mild and treated conservatively. Age, gender, comorbidity, SOD type, dilated common bile duct, presence of intact gallbladder, or opiate use were not related to the effect of treatment at the end of follow-up (p > 0.05 for all).</p> <p>Conclusions</p> <p>Patients with biliary SOD may be managed with a combination of endoscopic sphincterotomy (performed in those with dilated common bile duct) and medical therapy without manometry. The results of this approach with regards to symptomatic relief and ERCP complication rate are comparable to those previously published in the literature in cohorts of patients assessed by manometry.</p

GBA variants in REM sleep behavior disorder: a multicenter study

To study the role of GBA variants in the risk for isolated rapid-eye-movement (REM)-sleep behavior disorder (iRBD) and conversion to overt neurodegeneration