ד"ר רוני רמון-גונן

טלפון
דוא"ל
roni.ramon-gonen@biu.ac.il
תחומי עניין

Knowledge discovery, data mining, text mining, large language models, machine learning, unsupervised learning, and recommender systems

תחומי מחקר
    מחקר

    My primary research focuses on developing innovative methodologies to enhance the design, functionality, and quality of organizational information systems. My work spans diverse fields, including healthcare, organizational studies, and data science, with a strong emphasis on applying machine learning to improve clinical outcomes, decision making, and healthcare delivery.

    קורסים

    כריית נתונים, מדע הנתונים, כריית טקסט

    פרסומים

    Ramon-Gonen, R., & Gelbard, R. (2017). Cluster evolution analysis: Identification and detection of similar clusters and migration patterns. Expert Systems with Applications83, 363-378.

    Ramon-Gonen, R., Heart, T., Ben-Assuli, O., Shlomo, N., & Klempfner, R. (2022). Disease evolution and risk-based disease trajectories in congestive heart failure patients. Journal of Biomedical Informatics125, 103949.

    Gelbard, R., RamonGonen, R., Carmeli, A., Bittmann, R. M., & Talyansky, R. (2018). Sentiment analysis in organizational work: Towards an ontology of people analytics. Expert Systems35(5), e12289.

    Ramon-Gonen, R., Dori, A., & Shelly, S. (2023). Towards a practical use of text mining approaches in electrodiagnostic data. Scientific Reports13(1), 19483.

    Danay, L., Ramon-Gonen, R., Gorodetski, M., & Schwartz, D. G. (2024). Evaluating the effectiveness of a sliding window technique in machine learning models for mortality prediction in ICU cardiac arrest patients. International Journal of Medical Informatics191, 105565.

    Ben-Assuli, O., Ramon-Gonen, R., Heart, T., Jacobi, A., & Klempfner, R. (2023). Utilizing shared frailty with the Cox proportional hazards regression: Post discharge survival analysis of CHF patients. Journal of Biomedical Informatics140, 104340.

    Porter, I., Galam, B., & Ramon-Gonen, R. (2023). Emotion detection and its influence on popularity in a social network - based on the American TV series Friends. Social Network Analysis and Mining13(1), 123.

    תאריך עדכון אחרון : 12/09/2024