Sikora, Andrea

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

Principal Investigator

Sikora, Andrea

Project Name

Artificial Intelligence-Based Health Information Technology Tools to Optimize Critical Care Pharmacist Resources Through Adverse Drug Event 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

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

Principal Investigator

Sikora, Andrea

Project Name

Artificial Intelligence-Based Health Information Technology Tools to Optimize Critical Care Pharmacist Resources Through Adverse Drug Event Prediction

Evaluation of critical care pharmacist evening services at an academic medical center.

Citation

Chase AM, Forehand CC, Keats KR, Taylor AN, Jones TW, Sikora A. Evaluation of critical care pharmacist evening services at an academic medical center. Hosp Pharm. 2024 Apr;59(2):228-233. doi: 10.1177/00185787231207996. Epub 2023 Nov 1. PMID: 38450349; PMCID: PMC10913874.

Principal Investigator

Sikora, Andrea

Project Name

Artificial Intelligence-Based Health Information Technology Tools to Optimize Critical Care Pharmacist Resources Through Adverse Drug Event Prediction

Evaluation of critical care pharmacist evening services at an academic medical center.

Citation

Principal Investigator

Sikora, Andrea

Project Name

Machine Learning Validation of Medication Regimen Complexity for Critical Care Pharmacist Resource Prediction

Machine learning vs. traditional regression analysis for fluid overload prediction in the ICU.

Citation

Sikora A, Zhang T, Murphy DJ, Smith SE, Murray B, Kamaleswaran R, Chen X, Buckley MS, Rowe S, Devlin JW. Machine learning vs. traditional regression analysis for fluid overload prediction in the ICU. Sci Rep. 2023 Nov 10;13(1):19654. doi: 10.1038/s41598-023-46735-3. PMID: 37949982; PMCID: PMC10638304.

Principal Investigator

Sikora, Andrea

Project Name

Artificial Intelligence-Based Health Information Technology Tools to Optimize Critical Care Pharmacist Resources Through Adverse Drug Event Prediction

Machine Learning Validation of Medication Regimen Complexity for Critical Care Pharmacist Resource Prediction

Description

This research will develop and validate machine learning enhanced predictive models improving the allocation of critical care pharmacists to intensive care units to reduce adverse drug events.

Grant Number

R21 HS028485

Principal Investigator(s)

Sikora, Andrea

Artificial Intelligence-Based Health Information Technology Tools to Optimize Critical Care Pharmacist Resources Through Adverse Drug Event Prediction

Description

This research will use artificial intelligence and machine learning to create prediction tools integrated into visualization dashboards to guide critical care pharmacists in preventing adverse drug events.

Grant Number

R01 HS029009

Principal Investigator(s)

Sikora, Andrea