• Source: Scopus
  • Calculated based on no. of publications stored in Pure and citations from Scopus
20082019

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Personal profile

Research Biography

Dr Mallika is an Ophthalmologist with extensive clinical, teaching and research experience in both tertiary education and health sectors. Her PhD in item banking was conferred by Flinders University in 2018. She obtained her Medical degree at Madras Medical College, India and her specialist degree at the Regional Institute of Ophthalmology, Chennai, India. Prior to her doctoral degree, she was employed at the Department of Ophthalmology, Faculty of Medicine and Health Sciences, University Malaysia Sarawak as a Senior Lecturer as well as a Consultant Ophthalmologist at the Sarawak General Hospital. Throughout the 9 years in Malaysia, she achieved numerous academic and professional service excellence awards. She also embarked on various clinical and academic research projects. In 2014, she was invited to undertake the doctoral study by Flinders University and was offered two prestigious Australian scholarship (APA & IPRS). Between 2000 and 2004, she worked as a Consultant Ophthalmologist in India. Dr Mallika is a highly motivated researcher and a passionate educator, and her main research focus is on ocular diseases, artificial intelligence, ocular trauma, quality of life, PROMs and Rasch analysis.

Research Interests

Research interest include application of artificial intelligence in ophthalmology mainly corneal diseases. Dr Mallika is currently exploring the ability of artificial intelligence to differentiate bacterial, fungal and protozoal keratitis. One of the major problems in the management of infective keratitis is the accuracy of clinical and microbiological diagnoses. Making an accurate clinical diagnosis and determining the possible aetiology is critical for successful therapy. The artificial intelligence-based interpretation of infective keratitis may become a useful tool for clinicians to interpret the clinical features of infective keratitis more accurately and facilitate appropriate therapy. She was previously involved in designing an automated tool to detect advanced diabetic retinopathy changes using machine learning techniques.

Other research interest includes PROMs, quality of life, item bank, computerised adaptive testing and Rasch analysis. Her doctoral study involved development and validation of technologically advanced PROMs in the form of item banks implemented via computerised adaptive testing for retinal diseases using computer algorithms. The item bank implemented via the computerised adaptive testing requires fewer questions to provide precise and accurate assessment of quality of life impact. These item banks will enable clinicians and researchers to explore the impact of retinal diseases on quality of life. The item banks will have the potential to revolutionise the way patient-reported outcome measures are used in ophthalmology clinical settings and research.

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