Machine Learning

Effectiveness of a digital health intervention leveraging reinforcement learning: Results from the Diabetes and Mental Health Adaptive Notification Tracking and Evaluation (DIAMANTE) randomized clinical trial.

Citation
Aguilera A, Arévalo Avalos M, Xu J, Chakraborty B, Figueroa C, Garcia F, Rosales K, Hernandez-Ramos R, Karr C, Williams J, Ochoa-Frongia L, Sarkar U, Yom-Tov E, Lyles C. Effectiveness of a Digital Health Intervention Leveraging Reinforcement Learning: Results From the Diabetes and Mental Health Adaptive Notification Tracking and Evaluation (DIAMANTE) Randomized Clinical Trial. J Med Internet Res. 2024 Oct 8;26:e60834. doi: 10.2196/60834. PMID: 39378080; PMCID: PMC11496924.
Principal Investigator
Aguilera, Adrian
Project Name
Improving Diabetes and Depression Self-Management Via Adaptive Mobile Messaging

Cluster analysis driven by unsupervised latent feature learning of medications to identify novel pharmacophenotypes of critically ill patients.

Citation
Sikora A, Jeong H, Yu M, Chen X, Murray B, Kamaleswaran R. Cluster analysis driven by unsupervised latent feature learning of medications to identify novel pharmacophenotypes of critically ill patients. Sci Rep. 2023 Sep 20;13(1):15562. doi: 10.1038/s41598-023-42657-2. PMID: 37730817; PMCID: PMC10511715.
Principal Investigator
Sikora, Andrea
Project Name
Machine Learning Validation of Medication Regimen Complexity for Critical Care Pharmacist Resource Prediction

Machine learning based prediction of prolonged duration of mechanical ventilation incorporating medication data.

Citation
Sikora A, Zhao B, Kong Y, Murray B, Shen Y. Machine learning based prediction of prolonged duration of mechanical ventilation incorporating medication data. medRxiv [Preprint]. 2023 Sep 18:2023.09.18.23295724. doi: 10.1101/2023.09.18.23295724. PMID: 37790491; PMCID: PMC10543219.
Principal Investigator
Sikora, Andrea
Project Name
Machine Learning Validation of Medication Regimen Complexity for Critical Care Pharmacist Resource Prediction

Machine learning based prediction of prolonged duration of mechanical ventilation incorporating medication data.

Citation
Sikora A, Zhao B, Kong Y, Murray B, Shen Y. Machine learning based prediction of prolonged duration of mechanical ventilation incorporating medication data. medRxiv [Preprint]. 2023 Sep 18:2023.09.18.23295724. doi: 10.1101/2023.09.18.23295724. PMID: 37790491; PMCID: PMC10543219.
Principal Investigator
Sikora, Andrea
Project Name
Artificial Intelligence-Based Health Information Technology Tools to Optimize Critical Care Pharmacist Resources Through Adverse Drug Event Prediction

Long short-term memory model identifies ARDS and in-hospital mortality in both non-COVID-19 and COVID-19 cohort.

Citation
Chen JT, Mehrizi R, Aasman B, Gong MN, Mirhaji P. Long short-term memory model identifies ARDS and in-hospital mortality in both non-COVID-19 and COVID-19 cohort. BMJ Health Care Inform. 2023 Sep;30(1):e100782. doi: 10.1136/bmjhci-2023-100782. PMID: 37709302; PMCID: PMC10503386.
Principal Investigator
Gong, Michelle
Project Name
TREAT ECARDS: Translating Evidence into Action: Electronic Clinical Decision Support in Acute Respiratory Distress Syndrome

An AI-Directed CDS Tool to Reduce Iron Deficiency Anemia in Pregnancy: A Randomized Controlled Trial (AID-IDA Trial)

Description

This study will develop and establish the efficacy of an actionable predictive model to identify pregnant individuals at high risk for postpartum hemorrhage which can be used in combination with a clinical decision support tool to reduce the risk of hemorrhage-related morbidity and improve maternal health outcomes.

Grant Number
R21 HS030148
Principal Investigator(s)
Clapp, Mark A.

Using Large Language Models to Identify Social Determinants of Health to Enhance Healthcare Services and Equity

Description

This research explores using natural language processing and generative AI to capture and structure social determinants of health from patient narratives, aiming to improve data completeness and quality, enhance clinical decision support, and reduce the manual burden on clinical staff in routine care.

Grant Number
R21 HS029991
Principal Investigator(s)
Goss, Foster R.
Zhou, Li

Unsupervised machine learning analysis to identify patterns of ICU medication use for fluid overload prediction.

Citation
Keats K, Deng S, Chen X, Zhang T, Devlin JW, Murphy DJ, Smith SE, Murray B, Kamaleswaran R, Sikora A. Unsupervised machine learning analysis to identify patterns of ICU medication use for fluid overload prediction. medRxiv [Preprint]. 2024 Mar 22:2024.03.21.24304663. doi: 10.1101/2024.03.21.24304663. PMID: 38562806; PMCID: PMC10984037.
Principal Investigator
Sikora, Andrea
Project Name
Machine Learning Validation of Medication Regimen Complexity for Critical Care Pharmacist Resource Prediction

Unsupervised machine learning analysis to identify patterns of ICU medication use for fluid overload prediction.

Citation
Keats K, Deng S, Chen X, Zhang T, Devlin JW, Murphy DJ, Smith SE, Murray B, Kamaleswaran R, Sikora A. Unsupervised machine learning analysis to identify patterns of ICU medication use for fluid overload prediction. medRxiv [Preprint]. 2024 Mar 22:2024.03.21.24304663. doi: 10.1101/2024.03.21.24304663. PMID: 38562806; PMCID: PMC10984037.
Principal Investigator
Sikora, Andrea
Project Name
Artificial Intelligence-Based Health Information Technology Tools to Optimize Critical Care Pharmacist Resources Through Adverse Drug Event Prediction