![]() The future of precise personalised robotic physiotherapy Synthetic Mini-Chromosomes for Antibody Production Innovative Al-based Ophthalmologic Diagnosis ML-powered app and platform to identify skin changes over time Perinatal Life Support System: Integration of Enabling Technologies for Clinical TranslationĪnatomically Precise Revolutionary Implant for bone Conserving Osteoarthritis TreatmentĪl-based infectious diseases diagnosis in seconds The therapist in your pocket - Al assisted ecosystem for enabling a patient-centric approach to mental healthĪ revolutionary gait analysis system for smart injury and performance management ScreenCancer Mole Scanner - Easily accessible mole scanning service for early detection of skin cancer Smart and sensing robotic system for endovascular interventions with haptic feedback The first Clinically Validated Al-powered Diabetes AssistantīrainPatch - Breakthrough non-invasive brain stimulation using Alĭevice and method for automatized egg cell inspection and sorting Revolutionizing Healthcare by Tracking and Understanding Human Cells during Diseaseĭigital Enterprise Innovations for Bioimaging, Biosensing and Biobanking Industries The Brain Health Toolbox: Facilitating personalized decision-making for effective dementia prevention Microbiome Applications for Sustainable food systems through Technologies and EnteRprise Stimulating effects of Future and Emerging Technologies through communication and outreachĪ Universal Cyber Security Toolkit for Health-Care IndustryĮnhancing recovery from eating and weight disorders using mHealth and psychological theory In last decades, there has been growing potential usefulness of massive quantities of data, and its use, in transforming personal care, clinical care and health using artificial intelligence, blockchain and machine learning, with this context, the purpose of the present work is to review the usefulness of big data in the context of healthcare applications with the aim of encouraging the reader in the development and promotion of these technologies in the healthcare field, an issue that today is a reality and that encourages the use of multiple technologies for the search ( Table 1).Īrtificial Intelligence System for Multi-Cancer Detection Supportĭeep learning for mammography: Improving accuracy and productivity in breast cancer diagnosis The backbone of big data is made of the six “V” ( Figure 1). Therefore, Big Data was then defined as “the representation of information assets characterized by a high volume, velocity and variety to require specific technology and analytical methods for its transformation into value”. ![]() However, there was not an official definition of Big data, one of the accurate definitions was made by De Mauro et al. In the past decades, big data was based on the length and complexity of the information, essentially catalogued as information that cannot be stored nor analyzed by traditional means due to its enormous dimensions and convolutions, but later this information started to be stored, managed and analyzed through different technologies, that helped us to translate that information in a value resource to create, innovate and improve our daily activities. Thus, we are explaining the basis of these systems focused to the medical arena in order to encourage medical doctors, nurses, biotechnologies and other healthcare professions to be involved and create a more efficient and efficacy system. The healthcare system can be revolutionized using these different technologies. Perhaps, medical education and digital anatomy are unexplored fields that might be profitable to investigate as we are proposing. We also would like to demonstrate the different application and principal mechanisms of big data in the latest technologies known as blockchain and artificial intelligence, recognizing their benefits and limitations. ![]() ![]() The main objective of this review is to illustrate the state-of-art of big data in healthcare, its features and architecture. In the last decades big data has facilitating and improving our daily duties in the medical research and clinical fields the strategy to get to this point is understanding how to organize and analyze the data in order to accomplish the final goal that is improving healthcare system, in terms of cost and benefits, quality of life and outcome patient. ![]()
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