In Electronic Health Records (EHRs), much of valuable information regarding patients’ conditions is embedded in free text format. Natural language processing (NLP) techniques have been developed to extract clinical information from free text. One challenge faced in clinical NLP is that the meaning of clinical entities is heavily affected by modifiers such as negation. A negation detection algorithm, NegEx, applies a simplistic approach that has been shown to be powerful in clinical NLP. However, due to the failure to consider the contextual relationship between words within a sentence, NegEx fails to correctly capture the negation status of concepts in complex sentences. Incorrect negation assignment could cause inaccurate diagnosis of patients’ condition or contaminated study cohorts. We developed a negation algorithm called DEEPEN to decrease NegEx’s false positives by taking into account the dependency relationship between negation words and concepts within a sentence using Stanford dependency parser. The system was developed and tested using EHR data from Indiana University (IU) and it was further evaluated on Mayo Clinic dataset to assess its generalizability. The evaluation results demonstrate DEEPEN, which incorporates dependency parsing into NegEx, can reduce the number of incorrect negation assignment for patients with positive findings, and therefore improve the identification of patients with the target clinical findings in EHRs.

Primary surveillance of mixed-type IPMN may be a reasonable strategy in select patients. Diffuse MPD dilation, serum CA19-9, serum alkaline phosphatase, and absence of extrapancreatic cysts predict patients likely to progress during primary surveillance.

Background and Aims: Management of branch-duct intraductal papillary mucinous neoplasms (BDIPMNs) remains challenging. We determined factors associated with malignancy in BD-IPMNs and longterm outcomes.

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The Frey procedure is an appropriate, safe and effective technique for management of patients with chronic pancreatitis in the absence of neoplasia, based on long-term follow-up.