BANGAOIL, Ruth R.

BANGAOIL, Ruth R.

Ms. Ruth Rosario Bangaoil holds a degree in Medical Technology in the Philippines. She earned her Master’s in Medical Technology at the University of Santo Tomas. Currently, she serves as an academic staff in the Department of Medical Technology, Faculty of Pharmacy at the University of Santo Tomas, wherein she teaches Clinical Chemistry, Histopathology, Mycology, and Virology. In addition, she is a Clinical Faculty who handles Medical Technology interns assigned to various hospitals in the country. Moreover, her research has been published in international and local peer-reviewed journals. Her affiliations include membership with The Philippine Association of Medical Technologists, Inc. (PAMET) and the Philippine Association of Schools of Medical Technology and Public Health (PASMETH).

Updates

Three MedTech faculty members to serve in PASMETH 2023-2026 nat’l executive board

Three faculty members of the Department of Medical Technology of…

Academic Qualifications

Research Highlights

Research Interests

Academic Qualifications

  • Master of Science in Medical Technology – University of Santo Tomas
  • Bachelor of Science in Medical Technology – Far Eastern University Nicanor Reyes Memorial Foundation, Inc.

Research Highlights

Research Interests

Courses Handled

Major Recognitions

Professional Activities

Courses Handled

  • Clinical Chemistry
  • Mycology and Virology
  • Histopathology

Major Recognitions

Professional Activities

  • Member – Philippine Association of Medical Technologists, Inc.
  • Member – Philippine Association of Schools of Medical Technology and Public Health

Selected Publications

Selected Publications

  • Lugtu EJ, Ramos DB, Agpalza AJ, Cabral EA, Carandang RP, et al. (2022) Artificial neural network in the discrimination of lung cancer based on infrared spectroscopy. PLOS ONE 17(5): e0268329. https://doi.org/10.1371/journal.pone.0268329
  • Tomas RC, Sayat AJ, Atienza AN, Danganan JL, Ramos MR, et al. (2022) Detection of breast cancer by ATR-FTIR spectroscopy using artificial neural networks. PLOS ONE 17(1): e0262489. https://doi.org/10.1371/journal.pone.0262489 
  • Santillan, A., Tomas, R.C., Bangaoil, R. et al. Discrimination of malignant from benign thyroid lesions through neural networks using FTIR signals obtained from tissues. Anal Bioanal Chem 413, 2163–2180 (2021). https://doi.org/10.1007/s00216-021-03183-0