Location

Rochester, Minnesota

Contact

Enayati.Moein@mayo.edu

SUMMARY

Moein Enayati, Ph.D., is a research scientist in the field of artificial intelligence (AI) and machine learning (ML). He is enthusiastic about using his expertise to advance the science of healthcare delivery and disease diagnosis. Dr. Enayati's research interests include advanced data analytics, ML, natural language processing and noninvasive sensors for early disease identification and monitoring of people's health conditions.

Dr. Enayati strives to develop models, algorithms and tools that leverage multimodal clinical data to provide insight into complex health conditions. This improves the safety, efficiency and effectiveness of people's care.

Working in the Mayo Clinic Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Dr. Enayati makes significant efforts in developing novel technologies and algorithms that improve clinical practice and people's care.

He collaborates with clinical faculty and staff members from the cardiovascular medicine, emergency medicine and clinical genomics departments, the Center for Individualized Medicine, and the Mayo Clinic Comprehensive Cancer Center using exceptionally large sets of people's multimodal historical data. His research has resulted in numerous publications and multiple clinical decision systems integrated into the clinical practice inside and outside Mayo Clinic.

Focus areas

  • ML for early disease identification. Dr. Enayati uses different data analytics and ML techniques to study big datasets of clinical records to identify important factors in disease diagnosis. Individual-specific low-dimensional feature representations are being adopted for longitudinal monitoring of people's health conditions.
  • Text mining and natural language processing (NLP). One aspect of Dr. Enayati's research focuses on NLP, text processing and extraction of valuable clinical information from different semistructured and unstructured clinical notes. Research and development in the field of NLP provide automated alternatives for current time- and labor-intensive data extractions in clinical trials within different fields of practice.
  • Diagnostic errors in medicine. Dr. Enayati develops ML algorithms to identify specific instances of missed or delayed diagnoses. He analyzes causal relationships among potential individual-, provider- and system-related factors. Such studies help healthcare professionals determine root cause parameters and provide guidance to reduce or eliminate chances of recurrence.

Significance to patient care

Dr. Enayati's specific aim is to develop and adapt advanced AI and ML technologies that can directly enhance both individuals' care and clinical practice. Such efficient, reliable, generalizable and explainable AI-based solutions will help identify the root cause of complex clinical situations, reduce the chance of adverse events, enhance the diagnostic process and improve people's experience of clinical care.

PROFESSIONAL DETAILS

Administrative Appointment

  1. Senior Associate Consultant I-Research, Health Care Delivery Research, Kern Center for the Science of Health Care Delivery

Academic Rank

  1. Assistant Professor of Health Care Systems Engineering

EDUCATION

  1. Post Doctoral Researcher and Research Associate - Postdoctoral Research Associate at Kern Center, funded through an AHRQ grant to develop and utilize Machine learning techniques in prediction and detection of diagnosis errors in the ED Mayo Clinic in Rochester
  2. Ph.D. - PhD in Electrical Engineering and Computer Science Dissertation: “Machine Learning for Non-Invasive Monitoring of Vital Signs”, with a specific focus on fall detection and cardiovascular disease prediction in older adults in assisted living facilities. University of Missouri, Columbia
  3. MS - Industrial Engineering (Minored in System Management) Thesis: “Data Mining and Web Crawling in Recovering the Literature Gaps” Amirkabir University of Technology - Tehran Polytechnic
  4. BSc - Computer Science (Minored in Mathematics) Thesis: “Artificial Music Learning Agents Using Natural Language Processing” Amirkabir University of Technology - Tehran Polytechnic

Clinical Studies

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Publications

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BIO-20549202

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