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Health Sciences awards first Bongani Mayosi Medical Students Academic Prize

12 December 2020 | Story André Damons

Bongani Mayosi Prize Latest News — Drs Kaamilah Joosub (in front) and Lynette Upman, medical students in the Faculty of Health Sciences at the UFS, are the winners of the first Bongani Mayosi Medical Students Academic Prize for final-year medical students.

Two final-year medical students from the University of the Free State (UFS) became the first recipients of the prestigious Bongani Mayosi Medical Students Academic Prize which was bestowed on them 10 days before their graduation.

Drs Kaamilah Joosub and Lynette Upman, two final-year medical students in the Faculty of Health Sciences at the UFS are the first medical students from the university to be awarded the prize.This is the first year it has been awarded.

Drs Joosub and Upman received their awards at a function on Friday (4 December 2020) from Prof Hanneke Brits, Phase III chair and specialist in the Department of Family Medicine, on behalf of Prof Gert van Zyl, Dean of the Faculty of Health Sciences.

The Faculty of Health Sciences will host a virtual graduation on 14 December 2020.

Prestigious national award

The Bongani Mayosi Medical Students Academic Prize is a prestigious national award which aims to recognise final-year medical students who epitomise the academic, legendary, and altruistic life of Mayosi. The awards are presented to final-year MB ChB students from all South African medical faculties. Each student is allowed one vote for one classmate who, in their private opinion, best balances:

Academic achievement
Emotional intelligence ‑ good interpersonal skills
Social accountability ‑ the ability to respond helpfully to the needs of others

Winners are determined by the highest number of digital votes, with the first-prize winner receiving R6 000 and second prize coming in at R4 000.

Dr Lynette van der Merwe, undergraduate medical programme director in the School of Clinical Medicine at UFS, commented that Drs Joosub and Upman are worthy winners, as they have continuously exemplified the ideals recognised by this award during their undergraduate training.

The School of Clinical Medicine is very proud of its newest Kovsie doctors who successfully completed the academic year despite the immense challenges associated with the COVID-19 pandemic. This is thanks to the commitment and hard work of students and staff at the UFS.

Name behind the prize

The late Prof Bongani Mayosi was an outstanding doctor who rose rapidly through the ranks to become a top cardiologist, internationally recognised as a leading clinician scientist. He completed his undergraduate studies at the age of 22, having graduated cum laude in both the Bachelor of Medicine and Surgery (MB ChB) and Bachelor of Medical Sciences (BMedSci) degrees.

He trained as a physician and cardiologist at Groote Schuur Hospital and completed his doctorate at the University of Oxford in the UK. At the age of 38‚ he became the first black to be appointed professor and Head of the Department of Medicine at the University of Cape Town (UCT). In 2016, he was appointed Dean of the Faculty of Health Sciences at UCT. Before taking up his deanship, he completed the Advanced Management Programme at Harvard University in the US.

As a medical student Prof Mayosi excelled academically, was supportive of his classmates and enthusiastically involved in student residence committees and politics as well as community outreach programmes. As a researcher, he initiated an international programme of research focusing on solutions for poverty-related heart diseases and trained local clinician scientists and research leaders.

Prof Mayosi had an exceptional mixture of academic brilliance and vision; ambition and humility; kindness and generosity; passion and compassion; drive and empathy that complemented his ability to persuade and inspire others, which no doubt contributed to his 400 publications.

News Archive

Mathematical methods used to detect and classify breast cancer masses

2016-08-10

Description: Breast lesions Tags: Breast lesions

Examples of Acho’s breast mass
segmentation identification

Breast cancer is the leading cause of female mortality in developing countries. According to the World Health Organization (WHO), the low survival rates in developing countries are mainly due to the lack of early detection and adequate diagnosis programs.

Seeing the picture more clearly

Susan Acho from the University of the Free State’s Department of Medical Physics, breast cancer research focuses on using mathematical methods to delineate and classify breast masses. Advancements in medical research have led to remarkable progress in breast cancer detection, however, according to Acho, the methods of diagnosis currently available commercially, lack a detailed finesse in accurately identifying the boundaries of breast mass lesions.

Inspiration drawn from pioneer

Drawing inspiration from the Mammography Computer Aided Diagnosis Development and Implementation (CAADI) project, which was the brainchild Prof William Rae, Head of the department of Medical Physics, Acho’s MMedSc thesis titled ‘Segmentation and Quantitative Characterisation of Breast Masses Imaged using Digital Mammography’ investigates classical segmentation algorithms, texture features and classification of breast masses in mammography. It is a rare research topic in South Africa.

Characterisation of breast masses, involves delineating and analysing the breast mass region on a mammogram in order to determine its shape, margin and texture composition. Computer-aided diagnosis (CAD) program detects the outline of the mass lesion, and uses this information together with its texture features to determine the clinical traits of the mass. CAD programs mark suspicious areas for second look or areas on a mammogram that the radiologist might have overlooked. It can act as an independent double reader of a mammogram in institutions where there is a shortage of trained mammogram readers.

Light at the end of the tunnel

Breast cancer is one of the most common malignancies among females in South Africa. “The challenge is being able to apply these mathematical methods in the medical field to help find solutions to specific medical problems, and that’s what I hope my research will do,” she says.

By using mathematics, physics and digital imaging to understand breast masses on mammograms, her research bridges the gap between these fields to provide algorithms which are applicable in medical image interpretation.

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