Improved Classification Models to Distinguish Natural from Anthropic Oil Slicks in the Gulf of Mexico: Seasonality and Radarsat-2 Beam Mode Effects under a Machine Learning Approach

Distinguishing between natural and anthropic oil slicks is a challenging task, especially in the Gulf of Mexico, where these events can be simultaneously observed and recognized as seeps or spills.In this study, a powerful data analysis provided by machine learning (ML) methods was employed to develop, test, and implement a classification model (CM

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Disastrous cerebral and ocular vascular complications after cosmetic facial filler injections: a retrospective case series study

Abstract Soft tissue filler injections are among the most popular facial rejuvenation methods.Cerebral infarction and ophthalmic artery occlusion are rare and catastrophic complications, especially when facial cosmetic fillers are injected by inexperienced doctors.Radiologists and plastic surgeons need to increase their awareness of the complicatio

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Impacts of stimulus parameters and configurations on motor cortex direct electrical stimulation using intrinsic optical imaging: a pilot study

Abstract Background Motor cortex stimulation applied as a clinical treatment for neuropathic disorders for decades.With stimulation electrodes placed directly on the cortical surface, this neuromodulation method provides higher spatial resolution than other non-invasive therapies.Yet, the therapeutic effects reported were not in conformity with dif

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Preparing clinicians to be site investigators in multicenter clinical trials: A training program at an academic medical center

Clinical trials are essential in the translation of biomedical discoveries to new clinical interventions and therapeutics.Successful multisite clinical trials require qualified site investigators with an understanding of the full spectrum of processes and requirements from trial identification through closeout.New site investigators may be deterred

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