AI Guided Parenteral Nutrition Therapy After Hematopoietic Stem Cell Transplantation

Adults undergoing hematopoietic cell transplantation often develop serious complications that cause rapid nutritional decline. We developed and evaluated an AI approach to standardize intravenous nutrition (total parenteral nutrition, TPN) during this vulnerable period. Using real-world records from Stanford Health Care — 6,402 transplants between 2008 and 2025 — we analyzed 1,473 adults who received TPN, totaling 27,447 patient-days, linking each day's clinical state to the next day's prescription.

We created a library of 30 standardized TPN regimens and trained a model to recommend next-day dose adjustments based on laboratory data and the existing prescription (Pearson r ≈ 0.71). A reinforcement learning agent trained on past care selected dose adjustments with a higher composite score than the existing clinical policy. These results show that AI-guided TPN is feasible and may enhance bedside decision-making for adult transplant care, warranting prospective evaluation.