303 research outputs found

    Utilisation, availability and price changes of medicines and protection equipment for COVID-19 among selected regions in India : findings and implications

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    Background: COVID-19 has already claimed a considerable number of lives worldwide. However, there are concerns with treatment recommendations given the extent of conflicting results with suggested treatments and misinformation, some of which has resulted in increased prices and shortages alongside increasing use and prices of personal protective equipment (PPE). This is a concern in countries such as India where there have been high patient co-payments and an appreciable number of families going into poverty when members become ill. However, balanced against pricing controls. Community pharmacists play a significant role in disease management in India, and this will remain. Consequently, there is a need to review prices and availability of pertinent medicines during the early stages of the COVID-19 pandemic in India to provide future direction. Objective: Assess current utilisation and price changes as well as shortages of pertinent medicines and equipment during the early stages of the pandemic. Our Approach: Multiple approach involving a review of treatments and ongoing activities across India to reduce the spread of the virus alongside questioning pharmacies in selected cities from early March to end May 2020. Our Activities: 111 pharmacies took part, giving a response rate of 80%. Encouragingly, no change in utilisation of antimalarial medicines in 45% of pharmacies despite endorsements and for antibiotics in 57.7% of pharmacies, helped by increasing need for a prescription for dispensing. In addition, increased purchasing of PPE (over 98%). No price increases were seen for antimalarials and antibiotics in 83.8 and 91.9% of pharmacies respectively although shortages were seen for antimalarials in 70.3% of pharmacies, lower for antibiotics (9.9% of pharmacies). However, price increases were typically seen for PPE (over 90% of stores) as well as for analgesics (over 50% of pharmacies). Shortages were also seen for PPE (88.3%). Conclusion: The pandemic has impacted on utilisation and prices of pertinent medicines and PPE in India but moderated by increased scrutiny. Key stakeholder groups can play a role with enhancing evidenced-based approaches and reducing inappropriate purchasing in the future

    Guest Editorial: Large-Scale Multimedia Content Analysis on Social Media

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    EFFICACY OF DHATHU BUSHTI CHOORANAM IN THE MANAGEMENT OF MALE INFERTILITY WITH SPECIAL REFERENCE TO OLIGOSPERMIA - AN OPEN PILOT STUDY

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    Infertility is a common problem of new age couples. It is affecting them psychologically and also affecting the harmony of the family. Among infertility couples, 40% was caused by male partner particularly by oligospermia. Literally oligospermia means insufficient number of spermatozoa in semen, but significantly, it means that oligospermia is a medical condition characterized by the total sperm count less than 20 million/ml of ejaculate. Extensive clinical researches are going on worldwide to treat oligospermia by utilizing various natural sources like plants, mineral and animal origin.Siddha medicine is having many formulations to treat oligospermia, one among them is Dhathu bushti chooranam described in Noigalukku Siddha Parigaram –a Sasthiric siddha literature. 10 male partners of infertility couples attending Sool mahalir maruthuvam OPD of the Ayothidoss Pandithar Hospital, National Institute of Siddha, Tambaram sanatorium, Chennai-47 were recruited for this pilot study. All patients were treated with 10 gm of Dhathu bushti chooranam twice a day with milk for 90 days. All patients were subjected to complete semenogram on 0th and 90th day of treatment. Results were observed by analyzing the semenogram parameters. The ingredients of Dhathu bushti chooranam are Salamisiri, Nilapanai kizhangu,Thaneervittan kizhangu, Poonaikaali vidhai, Boomisarkkarai kizhangu and most of them are having good spermatogenesis and aphrodiasic activities, hence the author selected this drug for this study. The efficacy of the trial drug Dhathu bushti chooranam was appreciable and the drug may be taken for clinical trial in large number of population

    Adversarial Training Towards Robust Multimedia Recommender System

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    With the prevalence of multimedia content on the Web, developing recommender solutions that can effectively leverage the rich signal in multimedia data is in urgent need. Owing to the success of deep neural networks in representation learning, recent advance on multimedia recommendation has largely focused on exploring deep learning methods to improve the recommendation accuracy. To date, however, there has been little effort to investigate the robustness of multimedia representation and its impact on the performance of multimedia recommendation. In this paper, we shed light on the robustness of multimedia recommender system. Using the state-of-the-art recommendation framework and deep image features, we demonstrate that the overall system is not robust, such that a small (but purposeful) perturbation on the input image will severely decrease the recommendation accuracy. This implies the possible weakness of multimedia recommender system in predicting user preference, and more importantly, the potential of improvement by enhancing its robustness. To this end, we propose a novel solution named Adversarial Multimedia Recommendation (AMR), which can lead to a more robust multimedia recommender model by using adversarial learning. The idea is to train the model to defend an adversary, which adds perturbations to the target image with the purpose of decreasing the model's accuracy. We conduct experiments on two representative multimedia recommendation tasks, namely, image recommendation and visually-aware product recommendation. Extensive results verify the positive effect of adversarial learning and demonstrate the effectiveness of our AMR method. Source codes are available in https://github.com/duxy-me/AMR.Comment: TKD

    Identification of publicly available data sources to inform the conduct of Health Technology Assessment in India

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    Background: Health technology assessment (HTA) provides a globally-accepted and structured approach to synthesising evidence for cost and clinical effectiveness alongside ethical and equity considerations to inform evidence-based priorities. India is one of the most recent countries to formally commit to institutionalising HTA as an integral component of the heath resource allocation decision-making process. The effective conduct of HTA depends on the availability of reliable data. Methods: We draw from our experience of collecting, synthesizing, and analysing health-related datasets in India and internationally, to highlight the complex requirements for undertaking HTA, and explore the availability of such data in India. We first outlined each of the core data components required for the conduct of HTA, and their availability in India, drawing attention to where data can be accessed, and different ways in which researchers can overcome the challenges of missing or low quality data. Results: We grouped data into the following categories: clinical efficacy; cost; epidemiology; quality of life; service use/consumption; and equity. We identified numerous large local data sources containing epidemiological information. There was a marked absence of other locally-collected data necessary for informing HTA, particularly data relating to cost, service use, and quality of life. Conclusions: The introduction of HTA into the health policy space in India provides an opportunity to comprehensively assess the availability and quality of health data capture across the country. While epidemiological information is routinely collected across India, other data inputs necessary for HTA are not readily available. This poses a significant bottleneck to the efficient generation and deployment of HTA into the health decision space. Overcoming these data gaps by strengthening the routine collection of comprehensive and verifiable health data will have important implications not only for embedding economic analyses into the priority setting process, but for strengthening the health system as a whole

    COMPARATIVE PHYSICO-CHEMICAL AND PHYTO-CHEMICAL ANALYSIS OF TALISADI CHURNA WSR TO DIFFERENT MARKET SAMPLES

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    Talisadi Churna is a compound herbal formulation extensively used in disorders of upper respiratory tract and Gastro-intestinal tract. Formulation has greater demand due to its simple combination, therapeutic efficacy and methods of preparation and packaging due to which multiple companies prepare the formulation with due precision and safety evaluation. A current study was taken to evaluate in-house prepared sample of Talisadi Churna as per the AFI protocol and was compared to 3 different market samples. All the samples of Talisadi Churna were subjected to physico-chemical, preliminary phyto-chemical analysis and TLC. The study reveals that there is a significant difference is seen in the physico-chemical analysis and TLC, but there is no significant difference is seen in the preliminary phyto-chemical analysis

    NAIS: Neural Attentive Item Similarity Model for Recommendation

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    Item-to-item collaborative filtering (aka. item-based CF) has been long used for building recommender systems in industrial settings, owing to its interpretability and efficiency in real-time personalization. It builds a user's profile as her historically interacted items, recommending new items that are similar to the user's profile. As such, the key to an item-based CF method is in the estimation of item similarities. Early approaches use statistical measures such as cosine similarity and Pearson coefficient to estimate item similarities, which are less accurate since they lack tailored optimization for the recommendation task. In recent years, several works attempt to learn item similarities from data, by expressing the similarity as an underlying model and estimating model parameters by optimizing a recommendation-aware objective function. While extensive efforts have been made to use shallow linear models for learning item similarities, there has been relatively less work exploring nonlinear neural network models for item-based CF. In this work, we propose a neural network model named Neural Attentive Item Similarity model (NAIS) for item-based CF. The key to our design of NAIS is an attention network, which is capable of distinguishing which historical items in a user profile are more important for a prediction. Compared to the state-of-the-art item-based CF method Factored Item Similarity Model (FISM), our NAIS has stronger representation power with only a few additional parameters brought by the attention network. Extensive experiments on two public benchmarks demonstrate the effectiveness of NAIS. This work is the first attempt that designs neural network models for item-based CF, opening up new research possibilities for future developments of neural recommender systems

    Inherited blood disorders, genetic risk and global public health: framing 'birth defects' as preventable in India

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    This paper engages critically with the global assemblage framing sickle cell and thalassaemia disorders as a ‘global health crisis’; and the promise of genomics, largely DNA-based carrier/pre-conceptual screening, prenatal diagnosis with a view to terminations, deployed in framing a solution to these historically racialised spectrum of diseases as essentially preventable. Sickle cell and thalassaemia are recessively inherited, potentially life-threatening haemoglobin disorders with significant variation of severity, often needing life-long treatment. I argue that the re-classification of inherited blood disorders (IBDs) under ‘prevention and management of birth defects’ by the WHO in 2010 can be read as an ethical moment within the ‘globalising turn’ of IBDs and the use of genomics in addressing structural inequalities underpinning health in low- and middle-income countries. Using an Indian case study, the paper aims at first examining the language of risk through which genes and IBDs are mapped onto pre-existing populations (e.g. caste and tribe) as discrete, categories. Second, it discusses the likely social and ethical ramifications of classifying these recessive gene disorders as essentially preventable, despite cheaply available diagnostic tests and treatment options available in most countries in the South

    Should Research be Made Compulsory in Medical School?

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    oai:ojs2.jmrionline.com:article/2Healthcare decision-making is mostly reliant on evidence–based medicine. Building and upgrading skills in scientific reasoning and thinking amongst medical students has now became an important part of medical education. But due to unforeseen reasons, medical students in developing countries have no or very little opportunities to develop research skills and become evidence based physician-scientist. Moreover, there is also an alarming decline in the current number of physician-scientists, which also threatens the progress of translational medicine in the upcoming era. The compulsion of research work in residency, has no doubt, increased the quantity, but the quality has subsided. The only way, to improve the quality of research and medical evidence based health care, is by inculcating various research programs in school and motivating the professors and subsequently, the medical students. Many schools around the world have started various research training programs and the results are astonishing. Hence we suggest, instead of making research compulsory, there should be a location and school based research program which can help in developing interes
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