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

Table 2 Key artificial intelligence applications and methodologies in onco-critical care sepsis

Clinical application	Key AI/ML algorithms used	Primary data inputs	Demonstrated clinical impact
Early prediction of bacteremia in neutropenia	Random forest, XGBoost, Support vector machines	Routine hematological parameters (complete blood count + differential blood count trends), demographics[2,19]	Predicts bacterial growth 2-5 days prior to culture results, reducing indiscriminate use of broad-spectrum antibiotics[2]
Early warning of septic shock	DeepAISE (recurrent neural survival model), CNN-LSTM	Moving time-windows of vital signs, continuous EHR physiological data[15,17]	Identifies patient deterioration up to 12-24 hours before clinical onset, facilitating early administration of antimicrobials[20,25]
Integration of clinical notes	Latent Dirichlet allocation, natural language processing	Free-text physician progress notes, unstructured EHR data[17]	Captures physician intuition and nuanced clinical status; significantly improves accuracy of predictions 12-48 hours ahead of onset[17]
ICU mortality prediction	CatBoost, LightGBM, gradient boosting decision trees	Age, minimum blood urea nitrogen, urine output, red cell distribution width, metastasis status, SOFA/APS III[3,4]	Outperforms APACHE II/SOFA (AUC > 0.82-0.94); informs end-of-life and goals-of-care discussions[4,27,39]
Treatment optimization	Reinforcement learning digital twins	Historical treatment data, fluid balances, vasopressor responses[3,40]	Optimizes individual fluid resuscitation and vasopressor titration, preventing volume overload and reducing mortality[3]

AI: Artificial intelligence; ML: Machine learning; CNN: Convolutional Neural Network; LSTM: Long short-term memory; EHR: Electronic health record; ICU: Intensive care unit; SOFA: Sequential Organ Failure Assessment; APS: Acute Physiology Score; APACHE: Acute Physiology and Chronic Health Evaluation; AUC: Area under the curve.