Master Assignment
[D] Text mining to retrieve suspected cause of acute kidney injury from medical files
Type: MasterÂ
Period: TBD
Student: (Unassigned)
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Data type(s): Free text
Description: Acute Kidney Injury (AKI) is a common complication affecting up to 20% of hospitalized patients, leading to both short- and long-term issues such as prolonged hospital stays, chronic kidney insufficiency, and increased mortality. Early detection of AKI and identifying its underlying cause are critical for optimizing treatment and improving patient outcomes. However, the cause of AKI is often inconsistently documented by clinicians in free-text fields, making automatic extraction challenging. Natural Language Processing (NLP) techniques could be applied to extract the cause of AKI from these text records.
Goal: Develop a solution for extracting the cause of AKI from medical text files using NLP methods
Supervisor(s): Dion de Martines PhD candidate (ZGT)