Radiological reporting has generated large quantities of digital content within the electronic health record, which is potentially a valuable source of information for improving clinical care and supporting research. Although radiology reports are stored for communication and documentation of diagnostic imaging, harnessing their potential requires efficient and automated information extraction: they exist mainly as free-text clinical narrative, from which it is a major challenge to obtain structured data. Natural language processing (NLP) provides techniques that aid the conversion of text into a structured representation, and thus enables computers to derive meaning from human (ie, natural language) input. Used on radiology reports, NLP techniques enable automatic identification and extraction of information. By exploring the various purposes for their use, this review examines how radiology benefits from NLP. A systematic literature search identified 67 relevant publications describing NLP methods that support practical applications in radiology. This review takes a close look at the individual studies in terms of tasks (ie, the extracted information), the NLP methodology and tools used, and their application purpose and performance results. Additionally, limitations, future challenges, and requirements for advancing NLP in radiology will be discussed.

BackgroundMindfulness-based therapies are being used in a wide range of common chronic conditions in both treatment and prevention despite lack of consensus about their effectiveness in different patient categories.ObjectiveTo systematically review the evidence of effectiveness MBSR and MBCT in different patient categories.MethodsA systematic review and meta-analysis of systematic reviews of RCTs, using the standardized MBSR or MBCT programs. We used PRISMA guidelines to assess the quality of the included reviews and performed a random effects meta-analysis with main outcome measure Cohen’s d. All types of participants were considered.ResultsThe search produced 187 reviews: 23 were included, covering 115 unique RCTs and 8,683 unique individuals with various conditions. Compared to wait list control and compared to treatment as usual, MBSR and MBCT significantly improved depressive symptoms (d=0.37; 95%CI 0.28 to 0.45, based on 5 reviews, N=2814), anxiety (d=0.49; 95%CI 0.37 to 0.61, based on 4 reviews, N=2525), stress (d=0.51; 95%CI 0.36 to 0.67, based on 2 reviews, N=1570), quality of life (d=0.39; 95%CI 0.08 to 0.70, based on 2 reviews, N=511) and physical functioning (d=0.27; 95%CI 0.12 to 0.42, based on 3 reviews, N=1015). Limitations include heterogeneity within patient categories, risk of publication bias and limited long-term follow-up in several studies.ConclusionThe evidence supports the use of MBSR and MBCT to alleviate symptoms, both mental and physical, in the adjunct treatment of cancer, cardiovascular disease, chronic pain, depression, anxiety disorders and in prevention in healthy adults and children.