Nutrition for the sick preterm: can we make it more precise? Josef Neu

Extremely premature infants are more susceptible to adverse outcomes. This is why providing the best nutritional support through advanced techniques that can yield precise nutrition may help. Adverse outcomes among preterm infants, including growth failure, sepsis, intestinal dysfunction and diseases, and neurodevelopmental disorders are more likely prevented with specialized nutritional support by optimizing nutrition for the individual infant. Machine learning will likely play a pivotal role in this approach by analyzing medical databases used to customize feeding regimens for premature infants. This approach potentially allows healthcare providers make informed decisions with greater adaptation to the changing needs of individual infants.