Masoud Khani

About Me

Hello! I’m Masoud Khani, a Ph.D. candidate in Biomedical and Health Informatics at the University of Wisconsin-Milwaukee. My academic journey began with a Master’s degree in Computer Science, leading me to pursue impactful, interdisciplinary research at the intersection of technology and healthcare.

As a research assistant, I have worked on a wide range of projects aimed at improving patient care through AI-driven solutions. My primary focus has been on modeling Electronic Health Records (EHR) to predict clinical outcomes, uncover risk factors, and support personalized care. This involves designing advanced predictive models, leveraging both structured (tabular) and unstructured healthcare data, and enhancing model performance while ensuring interpretability.

I specialize in explainable AI (XAI) and interpretable machine learning to ensure that healthcare professionals can understand and trust the insights provided by AI systems. My research also explores human-in-the-loop systems, where medical experts collaborate with AI models in decision-making, thus integrating human expertise with machine learning to improve safety and reliability.

My technical expertise spans a wide range of domains, including:

Predictive Modeling with EHR Data for clinical applications
Explainable and Interpretable AI (XAI) for healthcare decision-making
Human-in-the-Loop Machine Learning systems to enhance trust and usability
Large Language Models (LLMs) and Generative AI to support medical text analysis
Medical Image Processing for diagnostic insights
Neural Signal Analysis to study brain and nervous system data
Social Determinants of Health analytics to identify key external factors affecting patient outcomes

In addition to research, I take pride in mentoring undergraduate and graduate students, helping them navigate complex research projects and develop technical expertise in data science, AI, and healthcare informatics. Seeing them grow has been one of the most rewarding parts of my career.

I am deeply passionate about advancing healthcare through cutting-edge technology and collaboration. By continuously pushing the boundaries of AI innovation, I aim to contribute to a future where data-driven solutions empower healthcare professionals to deliver more effective, efficient, and equitable care.

Google Scholar

News

Jan 21, 2025	Our Research paper "Risk Prediction and Interpretation for Fall Events Using Explainable AI and Large Language Models", was accepted at International Conference on Medical and Health Informatics (ICMHI 2025) conference.
Nov 24, 2024	Our paper titled “Advancing personalized healthcare: leveraging explainable AI for BPPV risk assessment” got published in Health Information Science and Systems.
Oct 22, 2015	A simple inline announcement.

Selected publications

Advancing Personalized Healthcare: Leveraging Explainable AI for BPPV Risk Assessment

Masoud Khani, Jake Luo, Mohammad Assadi Shalmani, and 3 more authors

2024

Bib HTML

@article{Khani2024BPPV,
  title = {Advancing Personalized Healthcare: Leveraging Explainable AI for BPPV Risk Assessment},
  author = {Khani, Masoud and Luo, Jake and Shalmani, Mohammad Assadi and Taleban, Amirsajjad and Adams, Jazzmyne and Friedland, David R},
  year = {2024},
}

Evaluation of Social Determinants of Health on Dysphagia Care Pathways at a Tertiary Care Facility

Maie M Zagloul, Jonathan M Bock, Joel H Blumin, and 6 more authors

2023

Bib HTML

@article{Maie2023dysphagia,
  title = {Evaluation of Social Determinants of Health on Dysphagia Care Pathways at a Tertiary Care Facility},
  author = {Zagloul, Maie M and Bock, Jonathan M and Blumin, Joel H and Friedland, David R and Adams, Jazzmyne A and Tong, Ling and Osinksi, Kristen I and Khani, Masoud and Luo, Jake},
  year = {2023},
}

A Risk Identification Model for Detection of Patients at Risk of Antidepressant Discontinuation

Ali Zolnour, Christina E Eldredge, Anthony Faiola, and 16 more authors

2023

Bib HTML

@article{Ali2023DrugDiscuntinuation,
  title = {A Risk Identification Model for Detection of Patients at Risk of Antidepressant Discontinuation},
  author = {Zolnour, Ali and Eldredge, Christina E and Faiola, Anthony and Khani, Masoud and Yaghoobzadeh, Yadollah and Foy, Doreen and Topaz, Maxim and Kharrazi, Hadi and Fung, Kin Wah and Fontelo, Paul and Davoudi, Anahita and Tabaie, Azade and Breitinger, Scott A. and Oesterle, Tyler S. and Rouhizadeh, Masoud and Zonnor, Zahra and Moen, Hans and Patrick, Timothy B and Zolnoori, Maryam},
  year = {2023},
}

Socioeconomic Disparities for Healthcare Utilization of Senior Adult Falls in Southeast Wisconsin, 2020-2022

Ling Tong, Masoud Khani, Bradley Taylor, and 4 more authors

2023

Bib HTML

@article{Tong2023Fall,
  title = {Socioeconomic Disparities for Healthcare Utilization of Senior Adult Falls in Southeast Wisconsin, 2020-2022},
  author = {Tong, Ling and Khani, Masoud and Taylor, Bradley and Osinski, Kristen and Adams, Jazzmyne and Friedland, David and Luo, Jake},
  year = {2023},
}

Association between body-mass index, patient characteristics, and obesity-related comorbidities among COVID-19 patients: A prospective cohort study

Ling Tong, Masoud Khani, Qiang Lu, and 3 more authors

2023

Bib HTML

@article{Tong2023association,
  title = {Association between body-mass index, patient characteristics, and obesity-related comorbidities among COVID-19 patients: A prospective cohort study},
  author = {Tong, Ling and Khani, Masoud and Lu, Qiang and Taylor, Bradley and Osinski, Kristen and Luo, Jake},
  year = {2023},
}

Impacts of Socioeconomic Status on Dentoalveolar Trauma.

C. N. Feller, J. A. Adams, D. R. Friedland, and 3 more authors

2023

Bib HTML

@article{Feller2023impacts,
  title = {Impacts of Socioeconomic Status on Dentoalveolar Trauma.},
  author = {Feller, C. N. and Adams, J. A. and Friedland, D. R. and Khani, M and Luo, J. and Poetker, D. M.},
  year = {2023},
}

Medical Image Segmentation Using Machine Learning

Masoud Khani

2021

Bib HTML