In the classification stage, the performance of five diverse deep learning models (e.g., Densenet121, ResNet34, ResNet50, VGG-16, and VGG-19) is assessed accurately to identify the healthiness of bean leaves. NX-5948 molecular weight The performance of the proposed framework is evaluated using a challenging and extensive dataset composed of 1295 images of three different classes (e.g., Healthy, Angular Leaf Spot, and Bean Rust). In the binary classification task, the best performance is achieved using the Densenet121 model with a CAR of 98.31%, Sensitivity of 99.03%, Specificity of 96.82%, Precision of 98.45%, F1-Score of 98.74%, and AUC of 100%. The higher CAR of 91.01% is obtained using the same model in the multi-classification task, with less than 2 s per image to produce the final decision.

To summarize data on atrial fibrillation (AF) detection rates and predictors across different rhythm monitoring strategies in patients with cryptogenic stroke (CS) or embolic stroke of undetermined source (ESUS).

MEDLINE, Embase, and Web of Science were searched to identify all published studies providing relevant data through July 6, 2020. Random-effects meta-analysis method was used to pool estimates.

We included 47 studies reporting on a pooled population of 8,215 patients with CS or ESUS. Using implantable cardiac monitor (ICM), the pooled rate of AF was 12.2% (95% CI 9.4-15.0) at 3months, 16.0% (95% CI 13.2-18.8) at 6months, 18.7% (95% CI 15.7-21.7) at 12months, 22.8% (95% CI 19.1-26.5) at 24months, and 28.5% (95% CI 17.6-39.3) at 36months. AF rates were significantly higher in patients with ESUS vs CS (22.0% vs 14.2%;

<0.001) at 6months, and in studies using Reveal LINQ vs Reveal XT ICM (19.1% vs 13.0%; p=0.001) at 12months. Using mobile cardiac outpatient telemetry (MCOT), the pooled rate of AF was 13.7% (95% CI 10.2-17.2) at 1month. Predictors of AF detection with ICM included older age, CHA

DS

-VASc score, left atrial enlargement, P wave maximal duration and prolonged PR interval.

The yield of ICM increases with the duration of monitoring. More than a quarter of patients with CS or ESUS will be diagnosed with AF during follow-up. About one in seven patients had AF detected within a month of MCOT, suggesting that a non-invasive rhythm monitoring strategy should be considered before invasive monitoring.

The yield of ICM increases with the duration of monitoring. More than a quarter of patients with CS or ESUS will be diagnosed with AF during follow-up. About one in seven patients had AF detected within a month of MCOT, suggesting that a non-invasive rhythm monitoring strategy should be considered before invasive monitoring.

Indigenous Australians experience a greater burden of AF. Whether this is in-part due to differences in arrhythmogenic structures that appear to contribute to AF differences amongst other ethnicities is not known.

We studied forty individuals matched for ethnicity and other AF risk factors. Computed tomography imaging was used to characterise left atrial (LA), pulmonary vein (PV), and left atrial appendage (LAA) anatomy.

There were no significant differences in LA diameters or volumes between Indigenous and non-Indigenous Australians. Similarly, we could not detect any consistent differences in PV number, morphology, diameters, or ostial characteristics according to ethnicity. LAA analyses suggested that Indigenous Australians may have a greater proportion of non chickenwing LAA type, and a tendency for eccentric, oval-shaped LAA ostia; however, there were no other differences seen with regards to LAA volume or depth. Indexed values for LA, PV and LAA anatomy corrected for body size were broadly similarwith AF, suggest that it is these conditions that are more likely responsible for the AF substrate in these individuals. Continued efforts should therefore be directed towards risk factor management in an attempt to prevent and minimise the effects of AF in Indigenous Australians.

Some people experience symptoms and negative outcomes derived from their persistent, excessive, and problematic engagement in pornography viewing (i.e., Problematic Pornography Use, PPU). Recent theoretical models have turned to different cognitive processes (e.g., inhibitory control, decision making, attentional bias, etc.) to explain the development and maintenance of PPU, but empirical evidence derived from experimental studies is still limited. In this context, the present systematic review aimed to review and compile the evidence around cognitive processes related to PPU.

A systematic review was performed in accordance with PRISMA guidelines to compile evidence regarding cognitive processes related to PPU. We retained and analyzed 21 experimental studies addressing this topic.

Studies were focused on four cognitive processes attentional bias, inhibitory control, working memory, and decision making. In brief, PPU is related to (a) attentional biases toward sexual stimuli, (b) deficient inhibitory control (in particular, to problems with motor response inhibition and to shift attention away from irrelevant stimuli), (c) worse performance in tasks assessing working memory, and (d) decision making impairments (in particular, to preferences for short-term small gains rather than long-term large gains, more impulsive choice patterns than non-erotica users, approach tendencies toward sexual stimuli, and inaccuracies when judging the probability and magnitude of potential outcomes under ambiguity).

This systematic review offers a comprehensive overview of the current state of knowledge regarding the cognitive features related to PPU, and points out new areas that warrants further research.

This systematic review offers a comprehensive overview of the current state of knowledge regarding the cognitive features related to PPU, and points out new areas that warrants further research.Social death is an important concept that should be considered in a wide range of patients, especially in chronic diseases. Despite, there is still no clear and comprehensive definition of social death in medicine. The present study was thus conducted with Rodgers’ evolutionary concept analysis method to identify the key features and provide a clear definition of social death in patients and understand its background and consequences. Considering the stages of concept analysis, an initial search was carried out in scientific databases (PubMed, Science Direct, Google Scholar, Magiran, and SID) without time limit until 2020. The search resulted in 400 articles in the first stage, which were screened according to the study objective and, all the items and points consistent with the concept’s attributes, antecedents, consequences, associated concepts, alternative terms and definition were extracted. According to the results of different studies, the attributes of social death in patients can be classified into three main themes The loss of social identity, loss of social relations (social isolation), and deficiencies related to the inefficiency of the body and various diseases.