Considerations for advancing nephrology research and practice through natural language processing

Much of medical data is buried in the free text of clinical notes and not captured by structured data, such as administrative codes. Natural language processing (NLP) can locate and use information that resides in unstructured free text. Chan et  al. demonstrate that NLP is sensitive for identifying symptoms in hemodialysis patients. These findings highlight the benefit NLP may bring to nephrology and should prompt discussion of important considerations for NLP system design and implementation.
Source: Kidney International - Category: Urology & Nephrology Authors: Tags: Commentary Source Type: research

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Condition:   Hemodialysis Intervention:   Sponsor:   Washington University School of Medicine Recruiting
Source: ClinicalTrials.gov - Category: Research Source Type: clinical trials
This study examined the association between oBPs and all‐cause mortality in G3B‐5D CKD. This is a population‐based cohort study including all subjects with an estimated glomerular filtration rate (eGFR) 
Source: Journal of Bone and Mineral Research - Category: Orthopaedics Authors: Tags: Original Article Source Type: research
Source: Journal of Renal Nutrition - Category: Urology & Nephrology Source Type: research
Source: Journal of Renal Nutrition - Category: Urology & Nephrology Source Type: research
Source: Journal of Renal Nutrition - Category: Urology & Nephrology Source Type: research
Source: Journal of Renal Nutrition - Category: Urology & Nephrology Source Type: research
Source: Journal of Renal Nutrition - Category: Urology & Nephrology Source Type: research
Source: Journal of Renal Nutrition - Category: Urology & Nephrology Source Type: research
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Source: International Journal of Nephrology - Category: Urology & Nephrology Tags: Int J Nephrol Source Type: research
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Source: International Journal of Nephrology - Category: Urology & Nephrology Tags: Int J Nephrol Source Type: research
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