University of Pittsburgh-Pittsburgh Campus · Mathematics & StatisticsHauskrecht Alerting Lab
Milos Hauskrecht · Pittsburgh, Pennsylvania
Research Focus
Dr. Milos Hauskrecht's lab at the University of Pittsburgh focuses on improving clinical care through advanced alerting systems that leverage electronic medical records (EMR) and machine learning. The lab is developing innovative ways to predict and alert healthcare providers to potential medical errors, especially in intensive care units (ICUs). By combining data-driven insights with human expertise, they aim to enhance patient safety and optimize clinical decision-making.
medical errorsmachine learningelectronic medical recordsclinical alerting systemsintensive care unitsAI in healthcarepatient safetydecision supportreal-time monitoring
Research Aims
5AIM 01Develop machine learning models to predict physician actions from EMR data.
AIM 02Enhance alerting systems using adaptive knowledge bases.
AIM 03Evaluate the impact of AI-based alerts on clinician behavior in ICUs.
AIM 04Conduct clinical trials to assess the effectiveness of real-time monitoring alerts.
AIM 05Integrate human feedback to improve alert appropriateness and usefulness.
Skills the Lab Values
machine learningdata analysisclinical trial designsoftware deployment in clinical settingsEMR data integrationstatistical analysisalgorithm developmentperformance evaluationhuman-in-the-loop systems
Output against the department
Publications211bottom 47% of dept.70th of 131
this lab
most publishedleast published
Citations4.9kbottom 36% of dept.84th of 131
this lab
most citedleast cited
Career totals from OpenAlex, compared against labs that share a department. A department spans everything from one paper to tens of thousands, so bar heights are on a log scale — otherwise the largest lab would flatten every other bar to a line.