AIMC Topic: Area Under Curve

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Deep Learning in Diagnosis of Maxillary Sinusitis Using Conventional Radiography.

Investigative radiology
OBJECTIVES: The aim of this study was to compare the diagnostic performance of a deep learning algorithm with that of radiologists in diagnosing maxillary sinusitis on Waters' view radiographs.

Predicting Emergency Visits and Hospital Admissions During Radiation and Chemoradiation: An Internally Validated Pretreatment Machine Learning Algorithm.

JCO clinical cancer informatics
PURPOSE: Patients undergoing radiotherapy (RT) or chemoradiotherapy (CRT) may require emergency department evaluation or hospitalization. Early identification may direct preventative supportive care, improving outcomes and reducing health care costs....

Machine learning without borders? An adaptable tool to optimize mortality prediction in diverse clinical settings.

The journal of trauma and acute care surgery
BACKGROUND: Mortality prediction aids clinical decision making and is necessary for quality improvement initiatives. Validated metrics rely on prespecified variables and often require advanced diagnostics, which are unfeasible in resource-constrained...

Statistical Learning Methods to Determine Immune Correlates of Herpes Zoster in Vaccine Efficacy Trials.

The Journal of infectious diseases
Using Super Learner, a machine learning statistical method, we assessed varicella zoster virus-specific glycoprotein-based enzyme-linked immunosorbent assay (gpELISA) antibody titer as an individual-level signature of herpes zoster (HZ) risk in the Z...

Predicting protein-protein interactions through sequence-based deep learning.

Bioinformatics (Oxford, England)
MOTIVATION: High-throughput experimental techniques have produced a large amount of protein-protein interaction (PPI) data, but their coverage is still low and the PPI data is also very noisy. Computational prediction of PPIs can be used to discover ...

Off-target predictions in CRISPR-Cas9 gene editing using deep learning.

Bioinformatics (Oxford, England)
MOTIVATION: The prediction of off-target mutations in CRISPR-Cas9 is a hot topic due to its relevance to gene editing research. Existing prediction methods have been developed; however, most of them just calculated scores based on mismatches to the g...

Macular Vessel Density and Ganglion Cell/Inner Plexiform Layer Thickness and Their Combinational Index Using Artificial Intelligence.

Journal of glaucoma
PURPOSE: To evaluate the relationship between macular vessel density and ganglion cell to inner plexiform layer thickness (GCIPLT) and to compare their diagnostic performance. We attempted to develop a new combined parameter using an artificial neura...

Understanding Clinical Mammographic Breast Density Assessment: a Deep Learning Perspective.

Journal of digital imaging
Mammographic breast density has been established as an independent risk marker for developing breast cancer. Breast density assessment is a routine clinical need in breast cancer screening and current standard is using the Breast Imaging and Reportin...

Improving Young Stroke Prediction by Learning with Active Data Augmenter in a Large-Scale Electronic Medical Claims Database.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Electronic medical claims (EMC) database has been successfully used for predicting occurrences of stroke and a variety of other diseases. However, inadequate predictive performances have been observed in cases of rare occurrences due to both insuffic...