Accuracy Of Intuition Research Articles

Molecular and Nonmolecular Imaging of Macrophages in Atherosclerosis.

Atherosclerosis is a major cause of ischemic heart disease, and the increasing medical burden associated with atherosclerotic cardiovascular disease has become a major public health concern worldwide. Macrophages play an important role in all stages of the dynamic progress of atherosclerosis, from its initiation and lesion expansion increasing the vulnerability of plaques, to the formation of unstable plaques and clinical manifestations. Early imaging can identify patients at risk of coronary atherosclerotic disease and its complications, enabling preventive measures to be initiated. Recent advances in molecular imaging have involved the noninvasive and semi-quantitative targeted imaging of macrophages and their related molecules in vivo, which can detect atheroma earlier and more accurately than conventional imaging. Multimodal imaging integrates vascular structure, function, and molecular imaging technology to achieve multi-dimensional imaging, which can be used to comprehensively evaluate blood vessels and obtain clinical information based on anatomical structure and molecular level. At the same time, the rapid development of nonmolecular imaging technologies, such as intravascular imaging, which have the unique advantages of having intuitive accuracy and providing rich information to identify macrophage inflammation and inform targeted personalized treatment, has also been seen. In this review, we highlight recent methods and research hotspots in molecular and nonmolecular imaging of macrophages in atherosclerosis that have enormous potential for rapid clinical application.

Juxtaposing inference capabilities of deep neural models over posteroanterior chest radiographs facilitating COVID-19 detection

Severe Acute Respiratory Syndrome Corona Virus 2 or SARS-CoV-2 (COVID-19) has affected 21 million people worldwide and is responsible for 0.75 million deaths (as of August 2020). Declared as a pandemic by the WHO, the virus has affected almost every country after originating in China articulating how contagious the virus is. With reasonable social measures, countries have already shown depreciation in coronavirus cases. This paper deals with detecting and distinguishing the COVID-19 disease from normal patients through frontal chest X-ray scans using Convolutional Neural Networks. Different combinations of parameters were used to train multiple CNNs and their behavior was noted. After thorough experimentation of different models, the best model which achieved an accuracy of 0.98 on the test set with a loss of 0.036 was nominated. The selected model’s more intuitive accuracy metrics were calculated and its intermediate convolutional neural activations and receiver-operating characteristics curve is shown.

Accuracy of intuition in clinical decision-making among novice clinicians.

To assess the reliance on intuitive and analytical approaches during clinical decision-making among novice clinicians and whether that reliance is associated with accurate decision-making. Nurse educators and managers tend to emphasize analysis over intuition during clinical decision-making though nurses typically report some reliance on intuition in their practice. We hypothesized that under certain conditions, reliance on intuition would support accurate decision-making, even among novices. This study utilized an experimental design with clinical complication (familiar vs. novel) and decision phase (cue acquisition, diagnosis and action) as within-subjects' factors, and simulation role (observer, family, auxiliary nurse and primary nurse) as between-subjects' factor. We examined clinical decision-making accuracy among final semester pre-licensure nursing students in a simulation experience. Students recorded their reasoning about emerging clinical complications with their patient during two distinct points in the simulation; one point involved a familiar complication and the other a relatively novel complication. All data were collected during Spring 2015. Although most participants relied more heavily on analysis than on intuition, use of intuition during the familiar complication was associated with more accurate decision-making, particularly in guiding attention to relevant cues. With the novel complication, use of intuition appeared to hamper decision-making, particularly for those in an observer role. Novice clinicians should be supported by educators and nurse managers to note when their intuitions are likely to be valid. Our findings emphasize the integrated nature of intuition and analysis in clinical decision-making.

The Importance of Starting Right: The Influence of Accurate Intuition on Performance in Salesperson–Customer Interactions

Salespeople make two types of judgments about customers in face-to-face interactions: those that are more intuitive and those that are more deliberative. The authors evaluate the influence of accurate intuitive and deliberative judgments on the performance of salespeople. To evaluate this influence, the authors employ matched survey, observational, and objective field data obtained before, during, and after salesperson–customer interactions. The results reveal that accurate intuitive judgments improve selling performance by enabling more appropriate initial sales strategies. These judgments not only help increase the effectiveness of salespeople's selling efforts but also reduce the amount of selling time, resulting in improved selling efficiency. However, performance is compromised when inaccurate deliberative judgments follow accurate intuitive judgments. The findings also identify different antecedents to judgment accuracy. Intuitive accuracy is influenced by domain-specific experience, similarity to the customer, and empathy for the customer, whereas listening skills and customer orientation influence deliberative accuracy.

Intuitive accuracy at the verbal level

Intuitive accuracy at the verbal level