Machine learning (ML) is a burgeoning field of medicine with huge resources being applied to fuse computer science and statistics to medical problems. Proponents of ML extol its ability to deal with large, complex and disparate data, often found within medicine and feel that ML is the future for biomedical research, personalized medicine, computer-aided diagnosis to significantly advance global health care. However, the concepts of ML are unfamiliar to many medical professionals and there is untapped potential in the use of ML as a research tool. In this article, we provide an overview of the theory behind ML, explore the common ML algorithms used in medicine including their pitfalls and discuss the potential future of ML in medicine.

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Both carotid endarterectomy (CEA) and carotid artery stenting (CAS) are common treatments for carotid artery stenosis. Several randomized controlled trials (RCTs) have compared CEA to CAS in the treatment of carotid artery stenosis. These studies have suggested that CAS is more strongly associated with periprocedural stroke; however, CEA is more strongly associated with myocardial infarction. Published longterm outcomes report that CAS and CEA are similar. A reduction in complications associated with CAS has also been demonstrated over time. The symptomatic status of the patient and history of previous CEA or cervical radiotherapy are significant factors when deciding between CEA or CAS. Numerous carotid artery stents are available, varying in material, shape and design but with minimal evidence comparing stent types. The role of cerebral protection devices is unclear. Dual antiplatelet therapy is typically prescribed to prevent in-stent thrombosis, and however, evidence comparing periprocedural and postprocedural antiplatelet therapy is scarce, resulting in inconsistent guidelines. Several RCTs are underway that will aim to clarify some of these uncertainties. In this review, we summarize the development of varying techniques of CAS and studies comparing CAS to CEA as treatment options for carotid artery stenosis. K E Y W O R D Scarotid artery atherosclerosis, carotid artery stenosis, carotid artery stenting, carotid endarterectomy, stroke, stroke prevention | 319 LAMANNA et AL.

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The objectives of the study were to determine whether diagnostic accuracy and reliability by on-call teams is affected by communicating chest radiograph (CXR) images via instant messaging on smartphones in comparison to viewing on a workstation. 12 residents viewed 100 CXR images each with a 24% positive rate for significant or acute findings sent to their phones via a popular instant messaging application and reported their findings if any. After an interval of 42 days they viewed the original DICOM images on personal computers and again reported their findings. There were no statistically significant differences in accuracy, agreement, sensitivity, specificity, positive predictive value or negative predictive value between desktop workstation viewed images and images sent via the mobile application. Media messaging is a useful adjunct for quick second opinions on radiological images, without significant decay in diagnostic accuracy. If technical, ethical and legal issues are addressed, it could be incorporated into practice as a useful adjunct.

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