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Bongile Mzenda

Researcher at Queen Alexandra Hospital

Publications -  9
Citations -  79

Bongile Mzenda is an academic researcher from Queen Alexandra Hospital. The author has contributed to research in topics: Fuzzy logic & Margin (machine learning). The author has an hindex of 4, co-authored 9 publications receiving 72 citations. Previous affiliations of Bongile Mzenda include St Mary's Hospital & University of Portsmouth.

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Analysis of regional radiotherapy dosimetry audit data and recommendations for future audits.

TL;DR: Recommendations are made for future audits, including an essential requirement to maintain the monitoring of basic fundamental dosimetry, such as MV photon and electron output, but audits must also be developed to include new treatment technologies such as image-guided radiotherapy and address the most common sources of error in radiotherapy.
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Performance assessment of the BEBIG MultiSource? high dose rate brachytherapy treatment unit

TL;DR: The results of this investigation found that the uncorrected transit doses lead to small errors in the delivered dose at the first dwell position, but the transit dose correction for other dwells was accurate within 0.2 cGy.
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A simulation technique for computation of the dosimetric effects of setup, organ motion and delineation uncertainties in radiotherapy

TL;DR: A novel simulation technique is introduced to incorporate delineation errors into radiotherapy treatment margins and combine them with organ motion and set-up errors to investigate the cumulative dosimetric effects in different tumour sites to deduce the possible margin reductions and dose escalation achievable with reduced uncertainties.
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Determination of target volumes in radiotherapy and the implications of technological advances: a literature review

TL;DR: It is recommended that well devised clinical trials should be conducted to investigate fully the efficacy of these new techniques, particularly in radiotherapy image guidance and adaptive radiotherapy, and validate any recommendations regarding the current clinical margins and impact on their continued clinical use.
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A fuzzy convolution model for radiobiologically optimized radiotherapy margins.

TL;DR: The margin derived using the fuzzy technique showed good agreement compared to current prostate margins based on the commonly used margin formulation proposed by van Herk et al, and has nonlinear variation above combined errors of 5 mm standard deviation.