Artificial intelligence for early sepsis detection and dynamic prognostication in onco-critical care

Figure 1 Conceptual workflow of artificial intelligence-driven sepsis prediction in oncology intensive care unit patients. Clinical data from critically ill cancer patients - including vital signs, laboratory parameters, and unstructured electronic health record data - are processed and integrated using machine learning and deep learning models. These models generate risk scores and early warning alerts that support clinical decision-making, including early intervention and goals-of-care discussions. Continuous feedback from clinicians enables model refinement and improved performance over time. ICU: Intensive care unit; EHR: Electronic health record; NLP: Natural language processing; AI: Artificial intelligence; ML: Machine learning; LGBM: Light gradient boosting machine; RNN: Recurrent neural network; LSTM: Long short-term memory.