Transforming healthcare with big data analytics: technologies, techniques and prospects.

In different studies in the field of healthcare, big data analytics technology has been shown to be effective in observing the behaviour of data, of which analysed to allow the discovery of relevant insights for strategy and decision making. The objective of this study is to present the results of a systematic review of the literature on big data analytics in healthcare, focussing in technologies, main areas and purposes of adoption. To reach its objective, the study conducts an exploratory research, through a systematic review of the literature, using the Methodi Ordinatio protocol supported by content analysis. The results reveal that the use of tools implies work performance at the clinical and managerial level, improving the cost-benefit ratio and reducing the time factor in the practice of the workforce in health services. Thus, this study hopes to contribute to the technological advancement of computational intelligence applied to healthcare.

Machine learning applied to healthcare: a conceptual review.

The technological inference in procedures applied to healthcare is frequently investigated in order to understand the real contribution to decision-making and clinical improvement. In this context, the theoretical field of machine learning has suitably presented itself. The objective of this research is to identify the main machine learning algorithms used in healthcare through the methodology of a systematic literature review. Considering the time frame of the last twenty years, 173 studies were mined based on established criteria, which allowed the grouping of algorithms into typologies. Supervised Learning, Unsupervised Learning, and Deep Learning were the groups derived from the studies mined, establishing 59 works employed. We expect that this research will stimulate investigations towards machine learning applications in healthcare.

Government Initiative in Brazilian Public Health: A Technology Transfer Analysis.

The objective of this research is to analyze the transfer of technology developed by the commercial and industrial compensation policy of the initiative of the Plan of Expansion of Radiotherapy of the Ministry of Health. The data of the organization subsidized by the Plan of Expansion of Radiotherapy were obtained through research documentary, interviews with professionals and participant observation. The methodological strategy consisted of a case study supported by a cross-sectional study, the internal environment was analyzed with variables found in the literature, allowing its comprehension in a certain hospital situation. The results revealed that the initiatives of introduction of radiotherapy equipment by the Expansion Plan suffered numerous confrontations within the contextual and organizational circumstances that affected its development and effectiveness. Given the struggles of the Expansion Plan at the tactical and operational levels of decision-making, there are challenges that require responses from organizations involved in the process to implement the trade agreement established by the compensation policy, with the initial stage being highlighted as a technology transfer process. Due to management skills and expertise, it gives you the paradigm status to be followed based on the relevant dimensions and indicators of the technology transfer analysis.

Life cycle assessment of medium-density fiberboard (MDF) manufacturing process in Brazil.

Brazil is one of the largest producers of medium-density fibreboard (MDF) in the world, and also the MDF has the highest domestic consumption and production rate in the country. MDF applications are highlighted into residential and commercial furniture design and also a wide participation in the building sector. This study aimed to propose ways of improving the environmental cradle-to-gate life-cycle of one cubic meter MDF panel by means of a life-cycle assessment (LCA) study. Complying with requirements of ISO 14040 and 14,044 standards, different MDF manufacturing scenarios were modelled using Umberto® v.5.6 software and the Ecoinvent v.2.2 life-cycle inventory (LCI) database for the Brazilian context. Environmental and human health impacts were assessed by using the CML (2001) and USEtox (2008) methods. The evaluated impact categories were: acidification, global warming, ozone layer depletion, abiotic resource depletion, photochemical formation of tropospheric ozone, ecotoxicity, eutrophication and human toxicity. Results identified the following hotspots: gas consumption at the thermal plant, urea-formaldehyde resin, power consumption, wood chip consumption and wood chip transportation to the plant. The improvement scenario proposals comprised the following actions: eliminate natural gas consumption at the thermal plant, reduce electrical power consumption, reduce or replace urea-formaldehyde resin consumption, reduce wood consumption and minimize the distance to wood chip suppliers. The proposed actions were analysed to verify the influence of each action on the set of impact categories. Among the results, it can be noted that a joint action of the proposed improvements can result in a total reduction of up to 38.5% of impacts to OD, 34.4% to AD, 31.2% to ET, and 30.4% to HT. Finally, MDF was compared with particleboard production in Brazil, and additional opportunities to improve the MDF environmental profile were identified.