Deep convolution neural network for screening carotid calcification in dental panoramic radiographs.

Ischemic stroke, a leading global cause of death and disability, is commonly caused by carotid arteries atherosclerosis. Carotid artery calcification (CAC) is a well-known marker of atherosclerosis. Such calcifications are classically detected by ultrasound screening.

Reply to van der Pluijm et al. Comment on "Weitzman et al. Resistance to Antimalarial Monotherapy Is Cyclic. 2022, , 781".

Thank you for the opportunity to respond to comments gracefully raised by van der Pluijm et al. [..

Resistance to Antimalarial Monotherapy Is Cyclic.

Malaria is a prevalent parasitic disease that is estimated to kill between one and two million people-mostly children-every year. Here, we query PubMed for malaria drug resistance and plot the yearly citations of 14 common antimalarials. Remarkably, most antimalarial drugs display cyclic resistance patterns, rising and falling over four decades.

Machine learning vs. classic statistics for the prediction of IVF outcomes.

Purpose: To assess whether machine learning methods provide advantage over classic statistical modeling for the prediction of IVF outcomes.

Methods: The study population consisted of 136 women undergoing a fresh IVF cycle from January 2014 to August 2016 at a tertiary, university-affiliated medical center. We tested the ability of two machine learning algorithms, support vector machine (SVM) and artificial neural network (NN), vs.

A hybrid model for evaluating exposure of the general population in Israel to air pollutants.

Exposure to air pollution is associated with a wide range of health effects, including increased respiratory symptoms, cancer, reproductive and birth defects, and premature death. Air quality measurements by standardized measuring equipment, although accurate, can only provide an estimate for part of the population, with decreasing accuracy further away from the monitoring sites. Estimating pollution levels over large geographical domains requires the use of air quality models which ideally incorporate air quality measurements.