AIMC Topic: Diagnostic Errors

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Comparison of machine and deep learning for the classification of cervical cancer based on cervicography images.

Scientific reports
Cervical cancer is the second most common cancer in women worldwide with a mortality rate of 60%. Cervical cancer begins with no overt signs and has a long latent period, making early detection through regular checkups vitally immportant. In this stu...

Recognition of Thyroid Ultrasound Standard Plane Images Based on Residual Network.

Computational intelligence and neuroscience
Ultrasound is one of the critical methods for diagnosis and treatment in thyroid examination. In clinical application, many reasons, such as large outpatient traffic, time-consuming training of sonographers, and uneven professional level of physician...

Effects of a Differential Diagnosis List of Artificial Intelligence on Differential Diagnoses by Physicians: An Exploratory Analysis of Data from a Randomized Controlled Study.

International journal of environmental research and public health
A diagnostic decision support system (DDSS) is expected to reduce diagnostic errors. However, its effect on physicians' diagnostic decisions remains unclear. Our study aimed to assess the prevalence of diagnoses from artificial intelligence (AI) in p...

Radiologists versus Deep Convolutional Neural Networks: A Comparative Study for Diagnosing COVID-19.

Computational and mathematical methods in medicine
The reverse transcriptase polymerase chain reaction (RT-PCR) is still the routinely used test for the diagnosis of SARS-CoV-2 (COVID-19). However, according to several reports, RT-PCR showed a low sensitivity and multiple tests may be required to rul...

Technology Acceptance of a Machine Learning Algorithm Predicting Delirium in a Clinical Setting: a Mixed-Methods Study.

Journal of medical systems
Early identification of patients with life-threatening risks such as delirium is crucial in order to initiate preventive actions as quickly as possible. Despite intense research on machine learning for the prediction of clinical outcomes, the accepta...

Machine learning in primary care: potential to improve public health.

Journal of medical engineering & technology
It is estimated that missed opportunities for diagnosis occur in 1 in 20 primary care appointments. This is not only detrimental to individual patients, but also to the healthcare system as health outcomes are affected and healthcare expenditure inev...

DZC DIAG: mobile application based on expert system to aid in the diagnosis of dengue, Zika, and chikungunya.

Medical & biological engineering & computing
Dengue, Zika, and chikungunya are epidemic diseases transmitted by the Aedes mosquito. These virus infections can be so severe to the point of bringing on mobility and neurological problems, or even death. Expert systems (ES) can be used as tools for...

Efficient and Effective Training of COVID-19 Classification Networks With Self-Supervised Dual-Track Learning to Rank.

IEEE journal of biomedical and health informatics
Coronavirus Disease 2019 (COVID-19) has rapidly spread worldwide since first reported. Timely diagnosis of COVID-19 is crucial both for disease control and patient care. Non-contrast thoracic computed tomography (CT) has been identified as an effecti...