AUTOMATIC ICD-10 CODING USING PRESCRIBED DRUGS DATA.

This article discusses the emerging trends and challenges related to automatic clinical coding. We introduce an automatic coding system, which assigns short ICD-10 codes (restricted to the first three symbols, which define the category of the disease) based only on drugs prescribed to patients. We show that even with limited input data, the accuracy levels are comparable to those achieved by entry-level clinical coders as depicted by Seyed Nouraei et al.

Massively-parallel sequencing assists the diagnosis and guided treatment of cancers of unknown primary.

The clinical management of patients with cancer of unknown primary (CUP) is hampered by the absence of a definitive site of origin. We explored the utility of massively-parallel (next-generation) sequencing for the diagnosis of a primary site of origin and for the identification of novel treatment options. DNA enrichment by hybridization capture of 701 genes of clinical and/or biological importance, followed by massively-parallel sequencing, was performed on 16 CUP patients who had defied attempts to identify a likely site of origin.