A program that will qualify you in the field of biomedical image analysis and the control of socio-health data, in order to optimize medical care" 

Far from applying mechanical and sanitary care, data analysis and biomedical imaging make it possible to improve the diagnosis for each individual case. The extensive collection of data available to healthcare centers can be managed quickly and easily thanks to Big Data, but, above all, it allows heterogeneous information from different centers to be contrasted.

Given the need, public health requires professionals who know how to respond to problems and can implement the latest tools. TECH has detected the demand for professionals by companies and, therefore, offers thispostgraduate diploma inBiomedical Image Analysis and Big Data in E-Health to graduates in Engineering who wish to update their knowledge in this field. Students who receive the program will have a Relearning methodology that will avoid long hours of study and will enable them to assimilate the concepts in a simple and progressive way. 

In addition, TECH is supported by a team of professionals who work in this field and who even have their own research in telemedicine. Thanks to their experience and the exhaustive and personalized tutoring they offer, students will be able to resolve their doubts at any time and place. Likewise, they will have downloadable content in different formats that will provide them with all the necessary information to guarantee their education. 

Thanks to TECH, you will learn about the applications of Big Data in public health, such as risk predictions or personalized medicine through biomarkers"

This postgraduate diploma in Biomedical Image Analysis and Big Data in E-Health contains the most complete and up-to-date educational program on the market. Its most notable features are:

• The development of practical cases presented by experts in biomedical imaging and databases 
• The graphic, schematic, and practical contents with which they are created, provide practical information on the disciplines that are essential for professional practice 
• Practical exercises where self-assessment can be used to improve learning
• Its special emphasis on innovative methodologies 
• Theoretical lessons, questions to the expert, debate forums on controversial topics, and individual reflection assignments 
• Content that is accessible from any fixed or portable device with an Internet connection 

Inquire into the direct relationship between surgical interventions and imaging techniques, delving into their usefulness for recognizing medical patterns" 

The program’s teaching staff includes professionals from the sector who contribute their work experience to this educational program, as well as renowned specialists from leading societies and prestigious universities. 

Its multimedia content, developed with the latest educational technology, will allow the professional a situated and contextual learning; that is, a simulated environment that will provide an immersive education programmed to learn in real situations. 

This program is designed around Problem-Based Learning, whereby the professional must try to solve the different professional practice situations that arise during the course. For this purpose, the student will be assisted by an innovative interactive video system created by renowned and experienced experts. 

Learn about the benefits of IoT in patient monitoring and care and understand its contribution to the rehabilitation of those affected"

Thanks to the knowledge that TECH will transmit to you, you will learn about the multiple advantages that IoT brings by communicating devices with each other"

The syllabus of thispostgraduate diploma in Biomedical Image Analysis and Big Data in E-Health aims to instruct engineers who have a technical background and wish to expand their knowledge towards medical imaging and the applications of artificial intelligence and the Internet of Things (IoT) in telemedicine. In just six months, TECH will provide students with technological knowledge applied to medicine through a 100% downloadable content-based modality, which will be available even without an Internet connection. In addition, the study has been approached in a dynamic way to arouse interest and project the students' performance.

A program designed for you to understand how tools like Machine Learning work and to apply artificial intelligence algorithms in your own research" 

General Objectives

• Develop key concepts of medicine that serve as a vehicle to understand clinical medicine 
• Determine the major diseases affecting the human body, classified by apparatus or systems, structuring each module into a clear outline of pathophysiology, diagnosis, and treatment 
• Determine how to obtain metrics and tools for healthcare management 
• Understand the basics of basic and translational scientific methodology 
• Examine the ethical and best practice principles governing the different types of research in health sciences 
• Identify and generate the means of funding, assessing and disseminating scientific research 
• Identify the real clinical applications of the various techniques 
• Develop the key concepts of computational science and theory 
• Determine the applications of computation and its implication in bioinformatics 
• Provide the necessary resources to practically apply all the concepts in the modules 
• Develop the fundamental concepts of databases 
• Determine the importance of medical databases 
• Delve into the most important techniques in research 
• Identify the opportunities offered by the IoT in the field of e-Health 
• Provide specialized knowledge of the technologies and methodologies used in the design, development and assessment of telemedicine systems 
• Determine the different types and applications of telemedicine 
• Delve into the most common ethical aspects and regulatory frameworks of telemedicine 
• Analyze the use of medical devices 
• Develop the key concepts of entrepreneurship and innovation in e-Health 
• Determine what a business model is and the types that exist 
• Collect e-Health success stories and mistakes to avoid 
• Apply the knowledge acquired to an original business idea 

Specific Objectives 

Module 1. Techniques, Recognition and Intervention using Biomedical Imaging

• Examine the fundamentals of medical imaging technologies 
• Develop expertise in radiology, clinical applications and physical fundamentals 
• Analyze ultrasound, clinical applications and physical fundamentals 
• Delve into tomography computed and emission tomography, clinical applications and physical fundamentals 
• Determine how to manage magnetic resonance imaging, clinical applications and physical fundamentals 
• Generate advanced knowledge of nuclear medicine, differences between PET and SPECT, clinical applications and physical fundamentals 
• Discriminate noise in the image, reasons for it and image processing techniques to reduce it 
• Present image segmentation technologies and explain their usefulness 
• Gain an in-depth understanding of the direct relationship between surgical interventions and imaging techniques 
• Establish the possibilities offered by artificial intelligence in the recognition of patterns in medical images, thereby furthering innovation in the sector 

Module 2. Big Data in Medicine: Massive Medical Data Processing

• Gain specialized knowledge of massive data acquisition techniques in biomedicine
• Analyze the importance of data pre-processing in Big Data 
• Determine the differences between the data derived from different massive data collection techniques, as well as their special characteristics in terms of pre-processing and handling 
• Provide ways of interpreting results from massive data analysis 
• Examine the applications and future trends in the field of Big Data in biomedical research and public health 

Module 3. Applications of Artificial Intelligence and the Internet of Things (IoT) in Telemedicine

• Propose communication protocols in different scenarios in the healthcare field 
• Analyze IoT communication, as well as its application areas in e-Health 
• Substantiate the complexity of artificial intelligence models in its use in healthcare
• Identify the optimization brought by parallelization in GPU-accelerated applications and its use in healthcare
• Present all the Cloud technologies available to implement e-Health and the IoT products, both in computing and communication 
   

Meet your goal, delve into radiology and learn about the tools involved in nuclear medicine such as SPECT and PET”