AIMC Topic: Diagnostic Errors

Clear Filters Showing 51 to 60 of 104 articles

Application of Deep Learning for Early Screening of Colorectal Precancerous Lesions under White Light Endoscopy.

Computational and mathematical methods in medicine
METHODS: We collected and sorted out the white light endoscopic images of some patients undergoing colonoscopy. The convolutional neural network model is used to detect whether the image contains lesions: CRC, colorectal adenoma (CRA), and colorectal...

Chances and challenges of machine learning-based disease classification in genetic association studies illustrated on age-related macular degeneration.

Genetic epidemiology
Imaging technology and machine learning algorithms for disease classification set the stage for high-throughput phenotyping and promising new avenues for genome-wide association studies (GWAS). Despite emerging algorithms, there has been no successfu...

Improved patient satisfaction and diagnostic accuracy in skin diseases with a Visual Clinical Decision Support System-A feasibility study with general practitioners.

PloS one
Patient satisfaction is an important indicator of health care quality, and it remains an important goal for optimal treatment outcomes to reduce the level of misdiagnoses and inappropriate or absent therapeutic actions. Digital support tools for diff...

Can AI outperform a junior resident? Comparison of deep neural network to first-year radiology residents for identification of pneumothorax.

Emergency radiology
PURPOSE: To (1) develop a deep learning system (DLS) using a deep convolutional neural network (DCNN) for identification of pneumothorax, (2) compare its performance to first-year radiology residents, and (3) evaluate the ability of a DLS to augment ...

[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...

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...

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...

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...