University of Pittsburgh-Pittsburgh Campus · Mathematics & StatisticsSepsis Decision-Making Lab
Lu Tang · Pittsburgh, Pennsylvania
Research Focus
Dr. Lu Tang's lab at the University of Pittsburgh focuses on enhancing the safety and effectiveness of machine learning algorithms in medical decision-making, specifically for sepsis treatment. By analyzing a large dataset from sepsis patients, the lab aims to create algorithms that can provide personalized treatment recommendations while managing risks and uncertainties. The research aims not only to develop novel methods but also to translate these improvements into user-friendly software for practical use in healthcare settings.
machine learningsepsismedical decision-makingpersonalized treatmentcausal inference
Research Aims
4AIM 01Develop a decision-learning algorithm that reduces adverse outcomes in sepsis treatment.
AIM 02Create an algorithm that mitigates suboptimal treatment actions due to unmeasured confounding effects.
AIM 03Enhance the safety and trustworthiness of machine learning-driven medical decisions.
AIM 04Translate novel algorithms into user-friendly software for practical medical use.
Skills the Lab Values
data analysisalgorithm developmentoptimization techniquescausal inference methodsprogramming in Python
Output against the department
Publications390top 24% of dept.31st of 131
this lab
most publishedleast published
Citations14ktop 33% of dept.43rd 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.