I am a dynamic professional with 8+ years of experience using data science and engineering methodologies to deliver tangible insights and enhance healthcare system outcomes. My research is focused on advancing AI techniques and using data-driven approaches to create deep learning algorithms for diverse clinical applications.
♦ Health Informatics ♦ Programming Skills ♦ Large-Scale Data Analysis ♦ Predictive Modeling ♦ Data Validation & Modeling ♦ Visualization Techniques ♦ Text-Based Data Analysis ♦ Machine Learning (ML) ♦ Deep Learning Methods (DL) ♦ Natural Language Processing (NLP) ♦ Generative Artificial Intelligence (AI) ♦ Large Language Models (LLM) ♦ OpenAI ♦ Prompt Engineering ♦ Recommender Systems ♦ Cross-Functional Partnership ♦ Communication Skills ♦ Environment Adaptability ♦ Organizational Skills ♦ Teamwork and Independent Work ♦ Problem-Solving Skills
- Ph.D., Informatics, University of Iowa, Iowa City, IA, USA, 2022-2025
- M.S, Informatics, University of Iowa, Iowa City, IA, USA, 2021-2022
- M.S, Medical Informatics, Tarbiat Modares University, Tehran, Iran,2013-2016
- B.S, Computer Software Engineering, Isfahan University, Isfahan, Iran, 2005-2010
Taught and facilitated discussion sessions for Introduction to Informatics and Python Programming courses. Provided one-on-one guidance and support to students, helping them understand complex ideas in informatics and develop strong Python coding skills
Collaborated with the National Center for Advancing Translational Sciences (NCATS) on the RARe-SOURCE™ project. https://raresource.nih.gov/ Implemented AI algorithms and utilized tools such as OpenAI models, LLaMA 3, LangChain, Ollama, Hugging Face, and RAG to search and analyze published literature for mentions of Farber diseases and associated genes.
Research Assistant, Computer Science/Informatics Department University of Iowa, Iowa City, IA, Fall 2021 – Spring 2025
Transform cancer symptom management through innovative integration of artificial intelligence (AI), resulting in unparalleled patient care and outcomes advancements. Provide compassionate and empathetic support to individuals grappling with cancerrelated symptoms and stressors, fostering resilience and enhanced well-being. Implement cutting-edge machine learning techniques and data-driven methodologies to develop personalized symptom management recommendations leading to improved patient care.
✌️ Accomplishments:
● Data Analysis & Statistical Modeling:
-Analyzed Electronic Health Records using Python and statistical methods, yielding fundamental insights that enhanced medical research and patient care.
-Identified predictors of symptom reporting agreement between patients and providers using deep learning and statistical techniques.
● Natural Language Processing (NLP) & Large Language Model (LLM):
-Collaborated closely with the research teams to develop an embeddings-augmented NLP system.
-Understanding the language in clinical notes in the electronic health records (EHR) system using NLP techniques and text analysis.
-Developing and comparing a pre-trained language model (like Bio-Clinical BERT and GPT) on customized EHRs to predict 13 cancer symptoms and Palliative care.
-Design specific prompts to guide GPT-4 in adapting to cancer symptom prediction and palliative care tasks.
● Mobile Application Development with AI Techniques:
-Contributed to developing the OASIS (Oncology Associated Symptoms & Individualized Strategies) mobile app, a tool designed to help people with cancer.
-Collaborated with colleagues to develop deep-learning algorithms for the app's recommendation system, predicting 14 cancer symptoms in over 18,000 patients.
● Assisted in A/B testing the OASIS prototype on 100 patients, assessing its real-world efficacy and user experience.
Other Project:
-Collaborated with a team to extract web article content, develop a sentiment classifier, and perform cluster and topic analysis to identify prevalent themes.
-Worked with a team to leverage Python-based tools and algorithms to enhance and innovate demand forecasting methodologies.
-Developed a heart disease classification AI system using traditional machine learning models.
✌️ Accomplishments:
● Collaborated closely with the business teams to develop Electronic Medical Records (EMR), Pharmacy Information Systems (PIS), and Laboratory Information Systems (LIS). This collaboration resulted in streamlined healthcare workflows, enhanced data management, and improved patient care delivery by more than 50%. ● Developed an Android application for the automated tracking of heart failure symptoms of over 3,000 heart disease patients in rural areas of Isfahan province.
✌️ Accomplishments:
● Designed and implemented an efficient Electronic Health Records (EHR) management dashboard system using Business Intelligence techniques to reduce the report response time by more than 68%. ● Trained and mentored 1500+ clinicians and healthcare providers using electronic health records and dashboards, contributing to organizational growth and success.
• N. Zeinali (Presenter), A. AlBashayreh, et al. “Comparison of BERT Implementations for Enhanced Cancer Symptoms Extraction from Electronic Health Records.” 2024 IEEE First International Conference on Artificial Intelligence for Medicine, Health and Care (AIMHC), Laguna Hills, CA, USA, 2024, pp. 18-19, doi: 10.1109/AIMHC59811.2024.00011.
• N. Zeinali, Stephanie Gilbertson-White et al. “Machine Learning Approaches to predict symptoms in people with cancer: A Systematic Review.” JMIR cancer,2024. doi: 10.2196/52322.
• N. Zeinali, S. White, et al. “Symptom-BERT: Enhancing Cancer Symptom Detection in EHR Clinical Notes.” Publication Pain, and symptom management,2024.
• A. AlBashayreh, N. Zeinali, et al. “Natural Language Processing Accurately Differentiates Cancer Symptom Information in EHR Narratives.” JCO clinical cancer Informatics,2024.
• S. White, N. Zeinali, et al., “Special Section on Patient-Reported Outcomes and Informatics: Predictors of Concordance Between Patient-Reported and Provider-Documented Symptoms in the Context of Cancer and Multimorbidity.” Under review, ACI,2024.
• A. Bandyopadhyay, N. Zeinali, et al. “Using real-world EHR data to predict the development of 12 cancer-related symptoms in multimorbidity. Predictive” Preparation for JAMIA,2024. • A. AlBashayreh, N. Zeinali, et al. “Leveraging Spiritual-BERT for Characterizing Spiritual Care Documentation in EHRs of Older Adults.” Preparation for Journal, 2024.
• N. Zeinali, A. AlBashayreh et al. "Comparing Fine-Tuning Strategies and Prompt Engineering in Large Language Models for Identifying Anxiety and Nausea in Patients with Cancer from Clinical Notes" Preparation for Journal, 2024.
• N. Zeinali, A. Asosheh, et al. “The Conceptual Model to Solve Problem of Interoperability in Health Information Systems.” 2016 8th International Symposium on Telecommunications (IST), 2016, pp. 684-689, doi: 10.1109/ISTEL.2016.7881909.
• Nazari E, Zeinali N, et al. “Application of Big Data Analysis in Healthcare Based on 6 Building Blocks of Health Systems: Survey”. Dokkyo Journal of Medical Sciences (DJMS) 2020.
• Shah Moradi M, Zeinali N, et al. “The Role of Social Networks in Healthcare: Applications and Limitations”. Journal of Health and Biomedical Informatics 2015; 2(2):124-128.
- Programming & Frameworks: Python, MATLAB, C/C++/C#, ASP.net, Android, JavaScript, HTML, XML
- Data Analysis: Pandas, NumPy
- Machine Learning and Deep Learning: Frameworks (like: TensorFlow, pytorch, sklearn, keras)
- NLP & LLM: NLTK, Spacy, BERT, GPT, LLaMa
- Cloud Platforms: Google Cloud, HPC cluster
- Databases: MS SQL Server, MS Access
- Statistics Tools: R, SPSS, SAS, STATA
- Visualization: Power BI
- Networking: TCP/IP, VLAN, router & switch configuration
- Operating Systems & Tools: Windows, Linux, Azure, VMware, Active Directory, server clustering
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Student Impact Grant(1000$), University of Iowa, Summer 2024
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AMIA 10*10 program funded (2000$) by Carver College of Medicine (CCOM), University of Iowa, Spring 2024
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Research and Travel GPSG Award (1250 $), University of Iowa, Spring 2024
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Research Assistant Grant (6000$), College of Nursing, University of Iowa, Spring 2024
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Publication Grant (2000$), University of Iowa, Winter2024
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Travel GSS Award (650$), Graduate College, University of Iowa, Winter2024
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Travel CS Award (400$), Computer Science Department, University of Iowa, Winter2024
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Recruitment Fellowship, IGPI (per year), University of Iowa, 2021- 2024
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Recruitment Fellowship, Tarbiat Modares University, 2013-2016
- 🔭 I’m currently working on this page.
- 🌱 I’m currently learning NLP ,Text analysis and Large Language Model like BERT, GPT, LLama, etc.
- 💬 Ask me about Machine Learning, Deep learning and NLP
- 📫 How to reach me: Nahid-zeinali@uiowa.edu
- last updated: May 15, 2024
