A transfer learning approach to drug resistance classification in mixed HIV dataset

Funding: This research is funded by the Tertiary Education Trust Fund (TETFund), Nigeria.As we advance towards individualized therapy, the ‘one-size-fits-all’ regimen is gradually paving the way for adaptive techniques that address the complexities of failed treatments. Treatment failure is associated with factors such as poor drug adherence, adverse side effect/reaction, co-infection, lack of follow-up, drug-drug interaction and more. This paper implements a transfer learning approach that classifies patients' response to failed treatments due to adverse drug reactions. The research is motivated by the need for early detection of patients' response to treatments and the generation of domain-specific datasets to balance under-represented classification data, typical of low-income countries located in Sub-Saharan Africa. A soft computing model was pre-trained to cluster CD4+ counts and viral loads of treatment change episodes (TCEs) processed from two disparate sources: the Stanford HIV drug resistant database (https://hivdb.stanford.edu), or control dataset, and locally sourced patients' records from selected health centers in Akwa Ibom State, Nigeria, or mixed dataset. Both datasets were experimented on a traditional 2-layer neural network (NN) and a 5-layer deep neural network (DNN), with odd dropout neurons distribution resulting in the following configurations: NN (Parienti et al., 2004) [32], NN (Deniz et al., 2018) [53] and DNN [9 7 5 3 1]. To discern knowledge of failed treatment, DNN1 [9 7 5 3 1] and DNN2 [9 7 5 3 1] were introduced to model both datasets and only TCEs of patients at risk of drug resistance, respectively. Classification results revealed fewer misclassifications, with the DNN architecture yielding best performance measures. However, the transfer learning approach with DNN2 [9 7 3 1] configuration produced superior classification results when compared to other variants/configurations, with classification accuracy of 99.40%, and RMSE values of 0.0056, 0.0510, and 0.0362, for test, train, and overall datasets, respectively. The proposed system therefore indicates good generalization and is vital as decision-making support to clinicians/physicians for predicting patients at risk of adverse drug reactions. Although imbalanced features classification is typical of disease problems and diminishes dependence on classification accuracy, the proposed system still compared favorably with the literature and can be hybridized to improve its precision and recall rates.Publisher PDFPeer reviewe

Mobile Phone Use for Empowerment and Well-Being of the Physically Challenged in Nigeria

Part 2: Digital Platforms for DevelopmentInternational audienceNational and economic benefits of mobile phone use in developing countries has been a well-articulated research domain over an extended period. This can be attributed to the ubiquitous nature of mobile phones and their increased penetration in developing nations. However, the potential benefits of mobile phones for empowerment and well-being of people with disability (PWD) has been ignored. This paper focuses on the well-being of the physically challenged in Nigeria and how mobile phones can be employed to empower them. The link between ICT and human development has been well researched, but minimal research has attempted to link ICT, mobile phone and disability using the Capability Approach as a theoretical lens. The critical realist ethnographic study approach is employed in this study to show how mobile phones can be used to empower and impact on the well-being of the physically challenged. Data were collected from the Adamawa skill acquisition center for persons with disability, Nigeria. It is argued that mobile phones have the capabilities to empower and impact on the well-being of the physically challenged. Thus, the findings illustrate that mobile phones play significant roles in the well-being and empowerment of the physically challenged

An holistic approach for counsellors: embracing multiple intelligences

This paper explores a range of therapeutic modalities used by counsellors of children and positions those modalities within Gardner’s theory of multiple intelligences. Research by O’Brien (1999) revealed that by drawing on a combination of preferred intelligences, children were able to enhance the dialogue between the unconscious and conscious, while strengthening the relationship between the counsellor and client. A number of useful counselling approaches are highlighted in working with children, particularly younger children who have not yet developed language sufficient for more formal counselling sessions. Suggestions that assist counsellors to operate across settings are explored