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Diagnostic Tests, Routine

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A doubly robust approach for cost-effectiveness estimation from observational data.

Statistical methods in medical research
Estimation of common cost-effectiveness measures, including the incremental cost-effectiveness ratio and the net monetary benefit, is complicated by the need to account for informative censoring and inherent skewness of the data. In addition, since t...

Egg Excretion does not Increase after Exercise: Implications for Diagnostic Testing.

The American journal of tropical medicine and hygiene
Children are frequently invited to exercise before micturition, as it is believed that this activity will result in higher egg excretion, and hence, increases sensitivity of microscopic diagnoses. However, the evidence of this recommendation is scan...

Predicting non-melanoma skin cancer via a multi-parameterized artificial neural network.

Scientific reports
Ultraviolet radiation (UVR) exposure and family history are major associated risk factors for the development of non-melanoma skin cancer (NMSC). The objective of this study was to develop and validate a multi-parameterized artificial neural network ...

Assessment of Functional Phosphatidylinositol 3-Kinase Pathway Activity in Cancer Tissue Using Forkhead Box-O Target Gene Expression in a Knowledge-Based Computational Model.

The American journal of pathology
The phosphatidylinositol 3-kinase (PI3K) pathway is commonly activated in cancer. Tumors are potentially sensitive to PI3K pathway inhibitors, but reliable diagnostic tests that assess functional PI3K activity are lacking. Because PI3K pathway activi...

Deep learning in radiology: An overview of the concepts and a survey of the state of the art with focus on MRI.

Journal of magnetic resonance imaging : JMRI
Deep learning is a branch of artificial intelligence where networks of simple interconnected units are used to extract patterns from data in order to solve complex problems. Deep-learning algorithms have shown groundbreaking performance in a variety ...

Artificial intelligence-based decision-making for age-related macular degeneration.

Theranostics
Artificial intelligence (AI) based on convolutional neural networks (CNNs) has a great potential to enhance medical workflow and improve health care quality. Of particular interest is practical implementation of such AI-based software as a cloud-base...

Supervised machine learning for the prediction of infection on admission to hospital: a prospective observational cohort study.

The Journal of antimicrobial chemotherapy
BACKGROUND: Infection diagnosis can be challenging, relying on clinical judgement and non-specific markers of infection. We evaluated a supervised machine learning (SML) algorithm for diagnosing bacterial infection using routinely available blood par...