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The potential of using artificial intelligence to improve skin cancer diagnoses in Hawai'i's multiethnic population.

Melanoma research
Skin cancer remains the most commonly diagnosed cancer in the USA with more than 1 million new cases each year. Melanomas account for about 1% of all skin cancers and most skin cancer deaths. Multiethnic individuals whose skin is pigmented underestim...

Machine learning for the identification of decision boundaries during the transition from radial to vertical growth phase superficial spreading melanomas.

Melanoma research
The objective of this study was to compute threshold values for the diameter of superficial spreading melanomas (SSMs) at which the radial growth phase (RGP) evolves into an invasive vertical growth phase (VGP). We examined reports from 1995 to 2019 ...

Novel Machine Learning Model Uncovers Key Prostate Cancer Pathways.

Cancer discovery
A biologically informed sparse neural network, P-NET, revealed previously unknown potential drivers.

A nine-hub-gene signature of metabolic syndrome identified using machine learning algorithms and integrated bioinformatics.

Bioengineered
Early risk assessments and interventions for metabolic syndrome (MetS) are limited because of a lack of effective biomarkers. In the present study, several candidate genes were selected as a blood-based transcriptomic signature for MetS. We collected...

Are rib fractures stable? An analysis of progressive rib fracture offset in the acute trauma setting.

The journal of trauma and acute care surgery
BACKGROUND: Rib fractures serve as both a marker of injury severity and a guide for clinical decision making for trauma patients. Although recent studies have suggested that rib fractures are dynamic, the degree of progressive offset remains unknown....

Automated Assessment of Brain CT After Cardiac Arrest-An Observational Derivation/Validation Cohort Study.

Critical care medicine
OBJECTIVES: Prognostication of outcome is an essential step in defining therapeutic goals after cardiac arrest. Gray-white-matter ratio obtained from brain CT can predict poor outcome. However, manual placement of regions of interest is a potential s...

Individual versus Group Calibration of Machine Learning Models for Physical Activity Assessment Using Body-Worn Accelerometers.

Medicine and science in sports and exercise
PURPOSE: We sought to determine if individually calibrated machine learning models yielded higher accuracy than a group calibration approach for physical activity intensity assessment.

Development and Validation of a Natural Language Processing Algorithm to Extract Descriptors of Microbial Keratitis From the Electronic Health Record.

Cornea
PURPOSE: The purpose of this article was to develop and validate a natural language processing (NLP) algorithm to extract qualitative descriptors of microbial keratitis (MK) from electronic health records.