Artificial intelligence (AI) aims to mimic human cognitive functions. It is bringing a paradigm shift to healthcare, powered by increasing availability of healthcare data and rapid progress of analytics techniques. We survey the current status of AI applications in healthcare and discuss its future. AI can be applied to various types of healthcare data (structured and unstructured). Popular AI techniques include machine learning methods for structured data, such as the classical support vector machine and neural network, and the modern deep learning, as well as natural language processing for unstructured data. Major disease areas that use AI tools include cancer, neurology and cardiology. We then review in more details the AI applications in stroke, in the three major areas of early detection and diagnosis, treatment, as well as outcome prediction and prognosis evaluation. We conclude with discussion about pioneer AI systems, such as IBM Watson, and hurdles for real-life deployment of AI.

Circulating tumor cells (CTCs) are shed from cancerous tumors, enter the circulatory system, and migrate to distant organs to form metastases that ultimately lead to the death of most patients with cancer. Identification and characterization of CTCs provides a means to study, monitor, and potentially interfere with the metastatic process. Isolation of CTCs from blood is challenging because CTCs are rare and possess characteristics that reflect the heterogeneity of cancers. Various methods have been developed to enrich CTCs from many millions of normal blood cells. Microfluidics offers an opportunity to create a next generation of superior CTC enrichment devices. This review focuses on various microfluidic approaches that have been applied to date to capture CTCs from the blood of patients with cancer.

Adding SWE features, especially the stiff rim sign at the display setting (<180 kPa), to conventional US has the potential to improve the differentiation of breast lesions.

The introduction of ultrasound into medical student education is well underway in many locations around the world, but is still in its infancy or has yet to begin in others. Proper incorporation of ultrasound education into medical training requires planning and resources, both capital and human. In this article, we discuss the state of the art of ultrasound in medical education throughout the world, as well as various methodologies utilized to improve student education and to incorporate ultrasound into every facet of training. Experiences from various educational systems and available evidence regarding the impact of ultrasound education are summarized. Representing multiple societies and specialties throughout the world, we discuss established modern as well as novel education structures and different successful approaches.