ORCID Profile
0000-0001-5208-1090
Current Organisations
RMIT University
,
University of Western Australia
,
Monash University
,
University of Queensland
,
Alfred Health
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In Research Link Australia (RLA), "Research Topics" refer to ANZSRC FOR and SEO codes. These topics are either sourced from ANZSRC FOR and SEO codes listed in researchers' related grants or generated by a large language model (LLM) based on their publications.
Data and information privacy | Computer vision and multimedia computation | Pattern recognition | Graph social and multimedia data |
Publisher: Elsevier BV
Date: 07-2022
Publisher: European Alliance for Innovation n.o.
Date: 13-07-2022
Publisher: Springer Science and Business Media LLC
Date: 04-09-2019
DOI: 10.1007/S40266-019-00704-6
Abstract: Our objective was to investigate associations between proton pump inhibitor (PPIs) use and infection-related hospitalizations among residents of long-term care facilities (LTCFs). This was a case-control study of residents aged ≥ 65 years admitted to hospital between July 2013 and June 2015. Residents admitted for infections (cases) and falls or fall-related injuries (controls) were matched for age (± 2 years), sex, and index date of admission (± 6 months). Conditional logistic regression was used to estimate crude and adjusted odds ratios (aORs) and 95% confidence intervals (CIs) for associations between PPI use and infection-related hospitalizations. Analyses were adjusted for age, sex, polypharmacy, diabetes, heart failure, chronic obstructive pulmonary disease, myocardial infarction, cerebrovascular accident, and concomitant use of cancer and immunosuppressant medications. Subgroup analyses were performed for high- and low/moderate-intensity PPIs and for respiratory and non-respiratory infections. Logistic regression was used to compare the odds of infection-related hospitalizations among users of high- and low/moderate-intensity PPIs. Overall, 181 cases were matched to 354 controls. Preadmission PPI use was associated with infection-related hospitalizations (aOR 1.66 95% CI 1.11-2.48). In subgroup analyses, the association was apparent only for respiratory infections (aOR 2.26 95% CI 1.37-3.73) and high-intensity PPIs (aOR 1.93 95% CI 1.23-3.04). However, the risk of infection-related hospitalization was not significantly higher among users of high- versus low/moderate-intensity PPIs (aOR 1.25 95% CI 0.74-2.13). Residents who use PPIs may be at increased risk of infection-related hospitalizations, particularly respiratory infections. Study findings provide further support for initiatives to minimize unnecessary PPI use in the LTCF setting.
Publisher: Springer International Publishing
Date: 2022
Publisher: Wiley
Date: 13-01-2022
DOI: 10.1111/AJAG.13038
Abstract: To determine i) the similarity of potentially inappropriate medications specified in and between existing explicit lists and ii) the availability in Australia of medications included on existing lists to determine their applicability to the Australian context. This systematic review identified explicit potentially inappropriate medication lists that were published on EMBASE (1974 – April 2021), MEDLINE (1946 – April 2021) and Elsevier Scopus (2004 – April 2021). The reference lists of seven previously published systematic reviews were also manually reviewed. Lists were included if they were explicit, and the most recent version and the complete list were published in English. Lists based on existing lists were excluded if no new items were added. Potentially inappropriate medications identified on each list were extracted and compared to the medications available on the Australian Register of Therapeutic Goods and Australian Pharmaceutical Benefits Schemes. Thirty‐five explicit published lists were identified. A total of 645 unique potentially inappropriate medications were extracted, of which 416 (64%) were available in Australia and 262 (41%) were subsided by the general Pharmaceutical Benefits Scheme. Applicability of each explicit list ranged from 50–96% according to medications available in Australia and 25‐83% according to medications available under subsidy. Pooling data from different lists may help to identify potentially inappropriate medications that may be applicable to local settings. However, if selecting a list for use in the Australian context, consideration should also be given to the intended purpose and setting for application.
Publisher: Public Library of Science (PLoS)
Date: 25-06-2021
DOI: 10.1371/JOURNAL.PONE.0253094
Abstract: Autism spectrum disorder (ASD) is a developmental disability characterized by persistent impairments in social interaction, speech and nonverbal communication, and restricted or repetitive behaviors. Currently Electroencephalography (EEG) is the most popular tool to inspect the existence of neurological disorders like autism biomarkers due to its low setup cost, high temporal resolution and wide availability. Generally, EEG recordings produce vast amount of data with dynamic behavior, which are visually analyzed by professional clinician to detect autism. It is laborious, expensive, subjective, error prone and has reliability issue. Therefor this study intends to develop an efficient diagnostic framework based on time-frequency spectrogram images of EEG signals to automatically identify ASD. In the proposed system, primarily, the raw EEG signals are pre-processed using re-referencing, filtering and normalization. Then, Short-Time Fourier Transform is used to transform the pre-processed signals into two-dimensional spectrogram images. Afterward those images are evaluated by machine learning (ML) and deep learning (DL) models, separately. In the ML process, textural features are extracted, and significant features are selected using principal component analysis, and feed them to six different ML classifiers for classification. In the DL process, three different convolutional neural network models are tested. The proposed DL based model achieves higher accuracy (99.15%) compared to the ML based model (95.25%) on an ASD EEG dataset and also outperforms existing methods. The findings of this study suggest that the DL based structure could discover important biomarkers for efficient and automatic diagnosis of ASD from EEG and may assist to develop computer-aided diagnosis system.
Publisher: Springer Nature Switzerland
Date: 2022
Publisher: Springer Nature Switzerland
Date: 2022
Publisher: Springer International Publishing
Date: 2021
Publisher: Elsevier BV
Date: 02-2021
Publisher: Elsevier BV
Date: 05-2016
DOI: 10.1016/J.SAPHARM.2016.06.003
Abstract: Polypharmacy is highly prevalent in residential aged care facilities (RACFs). Although polypharmacy is sometimes unavoidable, polypharmacy has been associated with increased morbidity and mortality. To identify and prioritize a range of potential interventions to manage polypharmacy in RACFs from the perspectives of health care professionals, health policy and consumer representatives. Two nominal group technique (NGT) sessions were convened in August 2015. A purposive s le (n = 19) of clinicians, researchers, managers and representatives of consumer, professional and health policy organizations were asked to nominate interventions to address the prevalence and appropriateness of medication use. Participants were then asked to prioritize five interventions suitable for possible implementation at the system level. Six of 16 potential interventions were prioritized highest for possible implementation in clinical practice, with two interventions prioritized as second highest. The top interventions in rank order were 'implementation of a pharmacist-led medication reconciliation service for new residents,' 'conduct facility-level audits and feedback to staff and health care professionals,' 'develop deprescribing scripts to assist clinician-resident discussion,' 'develop or revise prescribing guidelines specific to older people with multimorbidity in RACFs,' 'implement electronic medication charts and records' and 'better support Medication Advisory Committees (MACs) to address medication appropriateness.' This study prioritized a range of potential interventions that may be used to assist clinicians and policy makers develop a comprehensive strategy to manage polypharmacy in RACFs.
Publisher: Elsevier BV
Date: 07-2020
Publisher: European Alliance for Innovation n.o.
Date: 13-07-2018
Publisher: Public Library of Science (PLoS)
Date: 21-01-2022
DOI: 10.1371/JOURNAL.PONE.0262052
Abstract: The COVID-19 epidemic has a catastrophic impact on global well-being and public health. More than 27 million confirmed cases have been reported worldwide until now. Due to the growing number of confirmed cases, and challenges to the variations of the COVID-19, timely and accurate classification of healthy and infected patients is essential to control and treat COVID-19. We aim to develop a deep learning-based system for the persuasive classification and reliable detection of COVID-19 using chest radiography. Firstly, we evaluate the performance of various state-of-the-art convolutional neural networks (CNNs) proposed over recent years for medical image classification. Secondly, we develop and train CNN from scratch. In both cases, we use a public X-Ray dataset for training and validation purposes. For transfer learning, we obtain 100% accuracy for binary classification (i.e., Normal/COVID-19) and 87.50% accuracy for tertiary classification (Normal/COVID-19/Pneumonia). With the CNN trained from scratch, we achieve 93.75% accuracy for tertiary classification. In the case of transfer learning, the classification accuracy drops with the increased number of classes. The results are demonstrated by comprehensive receiver operating characteristics (ROC) and confusion metric analysis with 10-fold cross-validation.
Publisher: Springer Science and Business Media LLC
Date: 20-05-2022
DOI: 10.1007/S13755-022-00176-W
Abstract: We offer a framework for automatically and accurately segmenting breast lesions from Dynamic Contrast Enhanced (DCE) MRI in this paper. The framework is built using max flow and min cut problems in the continuous domain over phase preserved denoised images. Three stages are required to complete the proposed approach. First, post-contrast and pre-contrast images are subtracted, followed by image registrations that benefit to enhancing lesion areas. Second, a phase preserved denoising and pixel-wise adaptive Wiener filtering technique is used, followed by max flow and min cut problems in a continuous domain. A denoising mechanism clears the noise in the images by preserving useful and detailed features such as edges. Then, lesion detection is performed using continuous max flow. Finally, a morphological operation is used as a post-processing step to further delineate the obtained results. A series of qualitative and quantitative trials employing nine performance metrics on 21 cases with two different MR image resolutions were used to verify the effectiveness of the proposed method. Performance results demonstrate the quality of segmentation obtained from the proposed method.
Publisher: SAGE Publications
Date: 26-11-2021
Abstract: Falls are associated with considerable morbidity and mortality in aged care services and falls risk increasing drugs (FRIDs) are often overlooked as a contributor to falls. This study aims to investigate the association between the risk of falling and use of FRIDs from aged care services. Inverse-probability-weighted multinomial logistic regression was used to estimate the association between falls risk and regular FRIDs in 383 residents from six Australian aged care services. Overall, residents at high and low falls risk had similar prevalence of FRIDs. Prevalence of antipsychotics and sedative-hypnotics was low. Residents at high falls risk had higher adjusted odds of using ≥2 psychotropic medications (odds ratio [OR] = 1.75, 95% confidence interval [CI] = 1.17-2.61) and ≥2 medications that cause/worsen orthostatic hypotension (OR = 3.59, 95% CI = 2.27-5.69). High prevalence of FRIDs was mainly attributable to medications for which residents had clinical indications. Clinicians appeared to have largely avoided FRIDs that explicit criteria deem potentially inappropriate for high falls risk.
Publisher: Wiley
Date: 18-02-2021
DOI: 10.1111/AJAG.12913
Abstract: Older people living with mild cognitive impairment (MCI) have a slight but noticeable decline in their cognitive function, though do not meet the diagnostic criteria for dementia. MCI is controversial, with some saying it is a condition that does not require diagnosis, and others stating that it is a genuine clinical syndrome. Many people with MCI will improve, and most will not progress to dementia. Managing co‐morbidities and exercising are likely to be the best treatment options. With limited evidence for effective interventions and uncertainty as to the prognostic value of the condition, the benefit of diagnosing MCI remains unclear.
Publisher: Australasian College of Health Service Management
Date: 20-12-2022
DOI: 10.24083/APJHM.V17I3.1433
Abstract: Introduction: New Medicare Benefits Schedule (MBS) telehealth item codes were added in 2020 to allow Australians to gain access to medical services during COVID-19 lockdown restrictions. Previous studies have been conducted on the utilisation of specific MBS item codes however none have been conducted on all medical practitioner telehealth item codes. Objective: This retrospective epidemiological analysis aims to determine the utilisation rate of newly introduced medical practitioner telehealth MBS item codes and compare them with the usage of existing in-person item codes Methods: The utilisation of 319 MBS item codes were extracted from the Medicare Statistics Database between March 2020 to March 2021. Using count and population statistics a population adjusted rate was generated and a linear regression analysis undertaken. Results: A total of 199,059,309 in-person and telehealth services (Male, n=84,007,935 42.2%, Female, n=115,051,374 57.8%) were utilised during the study period. 147,697,104 were in-person compared to 51,191,898 telehealth services. In-person usage decreased by 27.5% while telehealth increased by 358.8%. In-person utilisation increased by 32.4% as the year continued while the telehealth utilisation decreased by 40.7%. There was a non-significant increase in total in-person item code utilisation (p=0.76) and a non-significant decrease (p=0.32) in the total telehealth item codes used Conclusion: There was initially increased usage of telehealth especially during lockdown restrictions. However, when lockdowns eased, usage of telehealth decreased while in-person increased. Regardless, telehealth item codes continued to be used despite changes to eligibility criteria and lockdown restrictions easing. Hence, it appears that patients are accepting of telehealth as a healthcare delivery method.
Publisher: Springer Science and Business Media LLC
Date: 26-03-2018
DOI: 10.1007/S40266-018-0537-3
Abstract: Residents of long-term care facilities (LTCFs) are at high risk of hospitalization. Medications are a potentially modifiable risk factor for hospitalizations. Our objective was to systematically review the association between medications or prescribing patterns and hospitalizations from LTCFs. We searched MEDLINE, Embase, Cumulative Index to Nursing and Allied Health Literature (CINAHL) and International Pharmaceutical Abstracts (IPA) from inception to August 2017 for longitudinal studies reporting associations between medications or prescribing patterns and hospitalizations. Two independent investigators completed the study selection, data extraction and quality assessment using the Joanna Briggs Institute Critical Appraisal Tools. Three randomized controlled trials (RCTs), 22 cohort studies, five case-control studies, one case-time-control study and one case-crossover study, investigating 13 different medication classes and two prescribing patterns were included. An RCT demonstrated that high-dose influenza vaccination reduced all-cause hospitalization compared with standard-dose vaccination (risk ratio [RR] 0.93 95% confidence interval [CI] 0.88-0.98). Another RCT found no difference in hospitalization rates between oseltamivir as influenza treatment and oseltamivir as treatment plus prophylaxis (treatment = 4.7%, treatment and prophylaxis = 3.5% p = 0.7). The third RCT found no difference between multivitamin/mineral supplementation and hospitalization (odds ratio [OR] 0.94 95% CI 0.74-1.20) or emergency department visits (OR 1.05 95% CI 0.76-1.47). Two cohort studies demonstrated influenza vaccination reduced hospitalization. Four studies suggested polypharmacy and potentially inappropriate medications (PIMs) increased all-cause hospitalization. However, associations between polypharmacy (two studies), PIMs (one study) and fall-related hospitalizations were inconsistent. Inconsistent associations were found between psychotropic medications with all-cause and cause-specific hospitalizations (11 studies). Warfarin, nonsteroidal anti-inflammatory drugs, pantoprazole and vinpocetine but not long-term acetylsalicylic acid (aspirin), statins, trimetazidine, digoxin or β-blockers were associated with all-cause or cause-specific hospitalizations in single studies of specific resident populations. Most cohort studies assessed prevalent rather than incident medication exposure, and no studies considered time-varying medication use. High-quality evidence suggests influenza vaccination reduces hospitalization. Polypharmacy and PIMs are consistently associated with increased all-cause hospitalization.
Publisher: Elsevier BV
Date: 03-2022
Publisher: Wiley
Date: 09-2019
DOI: 10.1111/AJAG.12676
Abstract: To systematically review literature reporting processes, impact and outcomes of medication review and reconciliation in Australian residential aged care facilities (RACFs). PubMed/MEDLINE, EMBASE, CINAHL, Informit Health and grey literature were searched from 1995 to July 2018. Studies reporting outcomes of a stand-alone medication review or reconciliation interventions in Australian RACFs were included. Thirteen studies investigated medication review, eight of which studied Residential Medication Management Reviews (RMMRs). Five studies reported that medication reviews identified an average of 2.7-3.9 medication-related problems (MRPs) per resident. One study reported medication reviews had no impact on quality of life, hospitalisation or mortality, but was not powered to assess these. Three studies reported general practitioners' acceptance of pharmacists' recommendations to resolve MRPs, ranging between 45 and 84%. Medication review may be a useful strategy to identify and prompt resolution of MRPs. However, the impact on clinical and resident-centred outcomes remains unclear.
Publisher: Springer Science and Business Media LLC
Date: 23-12-2022
DOI: 10.1186/S12903-022-02660-X
Abstract: Prescribing medicine is integral to clinical dentistry. Infective endocarditis may be rare but fatal if left untreated. As a result, judicious prescribing of antibiotics should be implemented due to potential. To our knowledge, no Australian study has examined dental students' knowledge and perceptions about antibiotic prophylaxis for dental procedures. Australian dental students were invited to undertake the survey comprising case vignettes to investigate their medication knowledge. A total of 117 responses were received. The questions were 12 clinically relevant questions and three perception-based questions. Results were analysed using descriptive statistics as well as the chi-squared test. The 117 respondents had a mean correct response of 7.34 ± 2.64 (range 3–12 out of 12). Out of 117 students, 89 (76%) answered more than half of the questions correctly. Only three students (3%) answered all the questions correctly. Nearly two-thirds felt that they knew about antibiotic prophylaxis used for dental procedures. Most respondents answered more than half, but not all, of the clinical questions correctly. It is crucial to highlight that dental student may never receive any more training on antimicrobial stewardship (AMS) at any point in their future careers. It may be ideal that this issue is addressed at the dental school. One way to target this is to potentially nationalised teaching delivery of dental AMS across Australia.
Publisher: Springer Science and Business Media LLC
Date: 23-06-2022
DOI: 10.1007/S11280-022-01076-5
Abstract: Knowledge graph, as an extension of graph data structure, is being used in a wide range of areas as it can store interrelated data and reveal interlinked relationships between different objects within a large system. This paper proposes an algorithm to construct an access control knowledge graph from user and resource attributes. Furthermore, an online learning framework for access control decision-making is proposed based on the constructed knowledge graph. Within the framework, we extract topological features to represent high cardinality categorical user and resource attributes. Experimental results show that topological features extracted from knowledge graph can improve the access control performance in both offline learning and online learning scenarios with different degrees of class imbalance status.
Publisher: Springer Science and Business Media LLC
Date: 17-08-2021
DOI: 10.1007/S41019-021-00167-Z
Abstract: Diabetic eye disease (DED) is a cluster of eye problem that affects diabetic patients. Identifying DED is a crucial activity in retinal fundus images because early diagnosis and treatment can eventually minimize the risk of visual impairment. The retinal fundus image plays a significant role in early DED classification and identification. An accurate diagnostic model’s development using a retinal fundus image depends highly on image quality and quantity. This paper presents a methodical study on the significance of image processing for DED classification. The proposed automated classification framework for DED was achieved in several steps: image quality enhancement, image segmentation (region of interest), image augmentation (geometric transformation), and classification. The optimal results were obtained using traditional image processing methods with a new build convolution neural network (CNN) architecture. The new built CNN combined with the traditional image processing approach presented the best performance with accuracy for DED classification problems. The results of the experiments conducted showed adequate accuracy, specificity, and sensitivity.
Publisher: Springer Nature Singapore
Date: 2023
Publisher: Springer International Publishing
Date: 2021
Publisher: Public Library of Science (PLoS)
Date: 14-11-2022
DOI: 10.1371/JOURNAL.PONE.0277555
Abstract: The diagnosis of neurological diseases is one of the biggest challenges in modern medicine, which is a major issue at the moment. Electroencephalography (EEG) recordings is usually used to identify various neurological diseases. EEG produces a large volume of multi-channel time-series data that neurologists visually analyze to identify and understand abnormalities within the brain and how they propagate. This is a time-consuming, error-prone, subjective, and exhausting process. Moreover, recent advances in EEG classification have mostly focused on classifying patients of a specific disease from healthy subjects using EEG data, which is not cost effective as it requires multiple systems for checking a subject’s EEG data for different neurological disorders. This forces researchers to advance their work and create a single, unified classification framework for identifying various neurological diseases from EEG signal data. Hence, this study aims to meet this requirement by developing a machine learning (ML) based data mining technique for categorizing multiple abnormalities from EEG data. Textural feature extractors and ML-based classifiers are used on time-frequency spectrogram images to develop the classification system. Initially, noises and artifacts are removed from the signal using filtering techniques and then normalized to reduce computational complexity. Afterwards, normalized signals are segmented into small time segments and spectrogram images are generated from those segments using short-time Fourier transform. Then two histogram based textural feature extractors are used to calculate features separately and principal component analysis is used to select significant features from the extracted features. Finally, four different ML based classifiers are used to categorize those selected features into different disease classes. The developed method is tested on four real-time EEG datasets. The obtained result has shown potential in classifying various abnormality types, indicating that it can be utilized to identify various neurological abnormalities from brain signal data.
Publisher: Springer Nature Singapore
Date: 2023
Publisher: Wiley
Date: 19-03-2022
DOI: 10.1002/JPPR.1802
Abstract: To investigate physical health outcomes associated with medications prescribed to manage chronic physical conditions in people living with dementia and determine whether a dementia diagnosis altered drug utilisation patterns for physical health conditions. Medline, Embase, Central and Scopus were searched 01/2011 to 12/2020. Experimental and observational studies, where participants with dementia using medications prescribed by doctors to prevent or treat one or more chronic comorbid physical condition, were compared to no intervention, usual care, or a non‐dementia comparison group. The outcomes of interest were clinically meaningful physical outcomes, and medication utilisation patterns. Ten studies met the inclusion criteria. All were of medium to high quality relative to their study design. Mixed findings were reported for ischemic stroke ( n = 3), all‐cause mortality ( n = 3) and bleeding‐related outcomes ( n = 2). This is likely due to the heterogeneity in exposures reported. One study found that people with dementia, receiving antidiabetic management, had a higher rate of severe hypoglycaemia compared to people without dementia. Medication utilisation pattern outcomes included oral anticoagulant use before stroke‐related hospitalisation ( n = 1), antithrombotic medication use before stroke‐related hospitalisation ( n = 1), cardiovascular medication use for secondary prevention of ischemic heart disease ( n = 1), antidepressant medication discontinuation ( n = 1), osteoporosis treatment ( n = 1), diabetic medication use ( n = 2), and antihypertensive medication discontinuation ( n = 1). This systematic review showed there is currently insufficient evidence to conclude that medication management in people with dementia should differ substantially to people without dementia. Comprehensive and high‐quality evidence is needed to improve confidence that medication prescribing achieves optimum clinical outcomes, quality of life, and benefit‐to‐risk determination in this vulnerable population.
Publisher: Elsevier BV
Date: 09-2021
DOI: 10.1016/J.MATURITAS.2021.06.004
Abstract: Many medicines have anticholinergic properties, which have previously been correlated with a range of adverse effects, including cognitive impairment, hallucinations and delirium. These effects are potentially of concern for people with dementia. This systematic review investigated the effect of anticholinergic medicines on the health outcomes of people with pre-existing dementia. Embase, Medline and the Cochrane Library were searched from January 2000 to January 2021. Studies were included if they matched the following criteria: (1) the intervention involved anticholinergic medications (2) the study was conducted in people with pre-existing dementia (3) there was at least one comparator group and (4) the outcome of interest was clinically measurable. A total of 14 studies met the inclusion criteria. Most studies used an anticholinergic burden scale to measure anticholinergic exposure. Five high-quality studies consistently identified a strong association between anticholinergic medications and all-cause mortality. Anticholinergics were also found to be associated with longer hospital length of stay in three studies. Inconsistent findings were reported for cognitive function (in 4 studies) and neuropsychiatric functions (in 2 studies). In single studies, anticholinergic medications were associated with the composite outcome of stroke and mortality, pneumonia, delirium, poor physical performance, reduced health-related quality of life and treatment modifications due to reduced treatment response or symptom exacerbation. While the evidence suggests that anticholinergic medication use for people with dementia has a strong association with all-cause mortality, the association with cognitive and other clinical outcomes remains uncertain. Hence, further studies are needed to substantiate the evidence for other outcomes.
Publisher: Oxford University Press (OUP)
Date: 09-05-2022
DOI: 10.1093/IJPP/RIAC033
Abstract: Pharmacists are known as medicine experts. Dentists can independently prescribe and administer medications related to dental conditions such as antimicrobials, anti-inflammatories and analgesics. However, little is known about pharmacists’ knowledge and perceptions of medicines prescribed for dentistry. Therefore, this study aimed to assess community pharmacists’ ability to identify the indications for dental prescriptions using hypothetical vignettes. Australian community pharmacists were invited through email and social media to undertake a web-based questionnaire consisting of nine case vignettes of dental prescriptions and their indicated uses in dental settings and two perception-based questions. The results were provided as a percentage of the correct answers to the case vignettes. In addition, Pearson chi-square tests were performed to examine associations between categorical variables. Of the 202 pharmacists who completed the questionnaire, the mean number of correct responses was 5 ± 2 (out of 9). More than three-quarters (78.5%) of pharmacists believed that thorough knowledge of prescriptions for dental ailments was necessary for safe and effective community pharmacy practice. In addition, nearly two-thirds (64.1%) felt confident that they could dispense medicines indicated for dental conditions safely and effectively. The knowledge demonstrated by participants through correct identification of the indications for dental prescription was less than optimal. Professional development courses for pharmacists in dental ailments could prove beneficial.
Start Date: 2022
End Date: 2024
Funder: Department of Foreign Affairs and Trade
View Funded ActivityStart Date: 07-2023
End Date: 06-2026
Amount: $352,968.00
Funder: Australian Research Council
View Funded Activity