Ms. Kira Phan | Machine Learning | California State University, San Bernardino | United States
Ms. Kira Phan is an emerging researcher and undergraduate scholar affiliated with the College of Natural Sciences at California State University, San Bernardino, where she is building a strong academic and research foundation in computational and data-driven sciences. She is currently pursuing undergraduate studies with a focus on applied computing, data analysis, and interdisciplinary scientific inquiry, demonstrating early commitment to research-oriented learning. Her academic journey is marked by active involvement in scholarly research, including meaningful participation in internationally co-authored studies that have resulted in peer-reviewed publication, an achievement that reflects both technical competence and academic maturity at an early career stage. Ms. Kira Phan has contributed to a Scopus-indexed journal article published in Computers (ISSN 2073-431X), where she applied machine learning techniques to the classification of textual medical notes, highlighting her capability in handling real-world healthcare data and complex analytical frameworks. Her research interests are centered on machine learning, medical text analytics, healthcare informatics, and artificial intelligence applications for clinical decision support, aligning closely with high-impact and globally relevant research domains. She has developed research skills in machine learning model evaluation, natural language processing, data preprocessing, collaborative research methodologies, and academic writing for international journals.
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Featured Publications:
Comparative Study of Machine Learning Models for Textual Medical Note Classification
Medical Informatics / Artificial Intelligence / Natural Language Processing
This study evaluates and compares multiple machine learning and NLP models for the classification of unstructured clinical text, highlighting performance trade-offs, feature representations, and implications for automated healthcare decision support.