Machine learning, an AI-powered tool that can be trained to detect patterns and analyze data, is central to the ongoing research funded by the NIH and led by Robinder Khemani, MD, the attending physician in pediatric intensive care at Children’s Hospital Los Angeles.
“There are many types of PVA, but we still don’t know which PVA subtypes are most harmful or are the most frequent,” Dr. Khemani said in a statement. “We need to develop a common set of definitions and measurements, especially for pediatric patients.”
For their research, a team of experts, including Dr. Khemani, will accumulate measurements from and then combine that information with an analysis of data from 350 other children in clinical trials, including one that is testing a ventilator strategy. This will then inform the team what adjustments, data and measurements to use when developing the machine learning algorithm.
“By the end of this project, we hope to have developed these algorithms and validate that they work in three different hospitals using data from many different children,” Dr. Khemani said in a statement. “Simultaneously we will build a tool to automatically detect PVA by analyzing ventilator data through machine-learning algorithms. We will test how well the tool helps providers to identify the minute-to-minute changes in patients and potentially alert the bedside team that an adjustment to the ventilator may be needed.”
Becker’s 3rd Annual Fall Chief Pharmacy Officer Summit is the top tier event that the people leading the future of pharmacy convene. This 3-day event is built specifically for Chief Pharmacy Officers and senior pharmacy leaders. The sessions examine the workforce, financial and clinical priorities shaping pharmacy today. Becker’s is where candid discussions flourish and new ideas thrive. Becker's 3rd Annual Fall Chief Pharmacy Officer Summit
