Dr. Fatemeh Shah-Mohammadi | Clinical Data Science | Best Researcher Award
Dr. Fatemeh Shah-Mohammadi at University of Utah, United States
Professional Profiles👨🎓
Early Academic Pursuits 🎓
Dr. Fatemeh Shah-Mohammadi completed her Master of Science in Electrical and Communication Engineering at Birjand University of Technology, where she laid the groundwork for her expertise in engineering and technology. She then pursued her PhD at Rochester Institute of Technology, specializing in Machine Learning. Her dissertation focused on “Machine Learning-enabled Resource Allocation in Underlay Cognitive Radio Networks,” demonstrating her commitment to applying advanced technologies in innovative ways.
Professional Endeavors 💼
Dr. Shah-Mohammadi currently serves as a Research Assistant Professor of Biomedical Informatics at the University of Utah, where she applies her skills in health informatics and clinical data science. Her professional journey includes significant roles as a Biostatistician II/NLP Engineer at Mount Sinai Health System and a postdoctoral fellow at the Icahn School of Medicine. These experiences have equipped her with a robust foundation in data analysis and machine learning applications across diverse domains.
Contributions and Research Focus 🔍
Dr. Shah-Mohammadi’s research primarily centers on the intersection of health informatics and machine learning. She has developed machine learning models that leverage cross-domain datasets to improve clinical outcomes. Notable projects include NLP-assisted pipelines for clinical note analysis and differential diagnosis, highlighting her dedication to enhancing healthcare delivery through technology.
Impact and Influence 🌍
Dr. Shah-Mohammadi’s work has significant implications for health informatics, particularly in the use of natural language processing (NLP) for clinical applications. Her publications in respected journals, such as the IEEE Open Journal of the Communications Society and Studies in Health Technology and Informatics, showcase her contributions to advancing knowledge in this field. Her research efforts aim to reduce diagnostic uncertainty and improve patient care outcomes, underscoring her influence in biomedical informatics.
Academic Cites 📚
Dr. Shah-Mohammadi’s scholarly output includes multiple peer-reviewed articles that have garnered citations and recognition within the academic community. Her ORCID and Google Scholar profiles further highlight her impact, showcasing a growing body of work that contributes to the fields of health informatics and machine learning.
Technical Skills 🛠️
Dr. Shah-Mohammadi is proficient in various technical areas, including:
- Machine Learning and Data Science
- Natural Language Processing
- Statistical Analysis
- Software Development for Biomedical Applications Her expertise enables her to build and implement sophisticated models that address real-world clinical challenges.
Teaching Experience 👩🏫
As an instructor at the University of Utah, Dr. Shah-Mohammadi teaches courses like “Generative AI in Healthcare” and “Intro to Programming.” Her teaching philosophy emphasizes the integration of cutting-edge technology with foundational principles, preparing students for future challenges in biomedical informatics.
Grants and Funding 💰
Dr. Shah-Mohammadi has actively sought and secured funding for her research initiatives. As the Principal Investigator for a project on automated live meta-analysis of clinical outcomes using generative AI, she demonstrates leadership in advancing research in health informatics. Her involvement as a co-investigator in various projects further highlights her collaborative spirit and dedication to impactful research.
Legacy and Future Contributions 🌟
Looking ahead, Dr. Shah-Mohammadi aims to continue her work at the forefront of health informatics, leveraging machine learning and NLP to drive innovations in clinical practice. Her commitment to research, teaching, and community engagement positions her as a leading figure in the field, poised to make lasting contributions to both academia and healthcare.
📖 Top Noted Publications
Addressing Semantic Variability in Clinical Outcome Reporting Using Large Language Models
Authors: Fatemeh Shah-Mohammadi, Joseph Finkelstein
Journal: BioMedInformatics
Year: 2024
Extraction of Substance Use Information From Clinical Notes: Generative Pretrained Transformer–Based Investigation
Authors: Fatemeh Shah-Mohammadi, Joseph Finkelstein
Journal: JMIR Medical Informatics
Year: 2024
Accuracy Evaluation of GPT-Assisted Differential Diagnosis in Emergency Department
Authors: Fatemeh Shah-Mohammadi, Joseph Finkelstein
Journal: Diagnostics
Year: 2024
Neural Network Cognitive Engine for Autonomous and Distributed Underlay Dynamic Spectrum Access
Authors: Fatemeh Shah-Mohammadi, Hatem Hussein Enaami, Andres Kwasinski
Journal: IEEE Open Journal of the Communications Society
Year: 2021
NLP-Assisted Differential Diagnosis of Chronic Obstructive Pulmonary Disease Exacerbation
Authors: Fatemeh Shah-Mohammadi, Joseph Finkelstein
Journal: Studies in Health Technology and Informatics
Year: 2024
Using Electronic Medical Records and Clinical Notes to Predict the Outcome of Opioid Treatment Program
Authors: W Cui, Fatemeh Shah-Mohammadi, Joseph Finkelstein
Journal: Healthcare Transformation with Informatics and Artificial Intelligence
Year: 2023