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Eric Clement Kotei Addison

Physics

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About

Mr. Eric Clement Kotei Addison is a Senior Lecturer in the Department of Physics, Faculty of Physical and Computational Sciences, College of Science. He has been lecturing in the Department since 1994. He is currently a Part-Time Lecturer at the Department of Medical Physics, School of Nuclear and Applied Sciences, University of Ghana, Legon. He is also a Medical Physicist and the Head Radiation Safety Officer at the Komfo Anokye Teaching Hospital, Kumasi.Mr. Kotei Addison is the Assistant National Coordinator for the International Atomic Energy Agency Technical Cooperation Project in the Establishment of the Nuclear Science Teaching Centre, Department of Physics, KNUST and also the AFRA Project Coordinator in Medical Physics. He lectures both Graduates and Undergraduates.Mr. Kotei Addison, at the Komfo Anokye Teaching Hospital - Oncology Directorate and Radiology Directorate, assisted in the Establishment and Installation of the Gamma Camera at the Nuclear Medicine Unit in the Korle-Bu Teaching Hospital. He played a supervisory role in the establishment of the New Radiotherapy/Nuclear Medicine Unit at Komfo Anokye Teaching Hospital. He also provided Medical Physics Clinical services to Komfo Anokye Teaching Hospital and Kwame Nkrumah University of Science and Technology.His research areas involve the fields of Medical Physics, Radiobiology, Health Physics, Biophysics, and Biomedical Engineering. In the field of Medical Physics, Mr. Addison assess and analyzes the radiation dose distribution in patients undergoing diagnostic radiology and computed tomography. Optimization and dose limitation is of international concern since radiation is a carcinogen. Radiotherapy research constructs verifiable High–Dose–Rate 192Ir brachytherapy models for accurate dose distribution. External beam radiotherapy dosimetry and treatment planning are the principal knowledge – based attributes of his characteristics.He has constructed a breast jig for treatment planning and routine treatment for all breast cancer patients at Oncology Directorate, Komfo Anokye Teaching Hospital.The research findings, in all areas of his research interests, have been published.

Research Summary

(inferred from publications by AI)

The researcher has conducted extensive research across multiple domains within health sciences, focusing on advanced radiotherapy techniques, patient safety, AI in cancer detection, and innovative methods for radon measurements. Their work explores the application of low-dose rate brachytherapy in addressing critical points in cervical cancer, as well as web-based incident analysis systems for radiation therapy. The researcher has also investigated deep transfer learning using ResNet18 and Resnet34 to detect breast cancer with high accuracy. Additionally, they have developed innovative imaging methods to measure radon concentration in groundwater, contributing to environmental impact assessments and public health accountability.

Research Themes

All Papers

Radiotherapy Planning and Peer Review in Sub-Saharan Africa: A Needs Assessment and Feasibility Study of Cloud-Based Technology to Enable Remote Peer Review and Training(2021)
Participant Evaluation of a Multi-disciplinary Oncology Preceptorship Training Program for Oncology Health Professionals from Kumasi, Ghana(2024)
The State of Clinical Medical Physics and Education in Ghana(2023)
Radiation-induced reactive oxygen species partially assemble neutrophil NADPH oxidase(2020)
Measurement of radon concentration in groundwater in the Ashanti region of Ghana(2018)
Dose Variation To Critical Points In Low Dose Rate Intracavitary Brachytherapy Of Cervical Cancer As Justification For Incident Learning(2022)
WEB-BASED RADIOTHERAPY INCIDENT ANALYSIS SYSTEM(2022)
Author response for "Investigating the Detection of Breast Cancer with Deep Transfer Learning Using Resnet18 and Resnet34"(2024)
Author response for "Investigating the Detection of Breast Cancer with Deep Transfer Learning Using Resnet18 and Resnet34"(2024)
Author response for "Investigating the Detection of Breast Cancer with Deep Transfer Learning Using Resnet18 and Resnet34"(2024)

Collaboration Network

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About This Profile

This profile is generated from publicly available publication metadata and is intended for research discovery purposes. Themes, summaries, and trajectories are inferred computationally and may not capture the full scope of the lecturer's work. For authoritative information, please refer to the official KNUST profile.