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Diagnostic Errors

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Sensor Fault Detection and Diagnosis Method for AHU Using 1-D CNN and Clustering Analysis.

Computational intelligence and neuroscience
This paper presents a fault detection and diagnosis (FDD) method, which uses one-dimensional convolutional neural network (1-D CNN) and WaveCluster clustering analysis to detect and diagnose sensor faults in the supply air temperature ( ) control loo...

Combining a gravitational search algorithm, particle swarm optimization, and fuzzy rules to improve the classification performance of a feed-forward neural network.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: A feed-forward neural network (FNN) is a type of artificial neural network that has been widely used in medical diagnosis, data mining, stock market analysis, and other fields. Many studies have used FNN to develop medical d...

Symptomatology differences of major depression in psychiatric versus general hospitals: A machine learning approach.

Journal of affective disorders
BACKGROUND: Symptomatology differences of major depressive disorder (MDD) in psychiatric and general hospitals in China leads to possible misdiagnosis. Looking at the symptomatology of first-visit patients with MDD in different mental health services...

MR-Forest: A Deep Decision Framework for False Positive Reduction in Pulmonary Nodule Detection.

IEEE journal of biomedical and health informatics
With the development of deep learning methods such as convolutional neural network (CNN), the accuracy of automated pulmonary nodule detection has been greatly improved. However, the high computational and storage costs of the large-scale network hav...

[Do artificial intelligence systems reason in the same way as clinicians when making diagnoses?].

La Revue de medecine interne
Clinical reasoning is at the heart of physicians' competence, as it allows them to make diagnoses. However, diagnostic errors are common, due to the existence of reasoning biases. Artificial intelligence is undergoing unprecedented development in thi...