Acute kidney injury (AKI) affects up to 20% of hospitalized Veterans and is strongly associated with morbidity and death. AKI is a diverse condition and timely and accurate diagnosis of the type of AKI is critical to begin appropriate therapies, especially those causes that require specific treatments beyond general supportive care. Yet, there are still significant gaps in the initial evaluation of AKI among hospitalized patients. Clinical decision support systems (CDSS) have shown promise to address these barriers, but most consist of simple alerting schemes and general care recommendations provided at a single point in time. The goal of this proposal is to develop and test the feasibility and usability of a rule-based and Artificial Intelligence-assisted precision CDSS tool (PRECISE-AKI) that can provide cognitive support to improve timely initial diagnostic evaluation of AKI.