- UAB Master's Degree (Continuing Education)
- Code: 4291/5
- 5th edition
- Modality: Online
- Credits: 60 ECTS
- Start date: 23/09/2024
- Finish date: 30/09/2026
- Places: 30
- Orientation: Professional
- Price: 5880 €
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Special price 5292 €
Group of application:
- Teaching language: Spanish
We are experiencing a revolution so profound that it will possibly surpass the invention of the steam engine, the train, electricity or mass production in the magnitude of the changes it will bring. This Fourth Industrial Age gravitates around artificial intelligence (AI), robotics and the Big date, advocates a profound revolution that is already visible in the way we live and work, perhaps even in the way we see ourselves as humans.
This revolution will also affect medicine. The same medicine is in a certain way in a moment of crisis. As a profession, despite the extraordinary advances in the art and science of medicine in the last four decades, it frequently presents limitations in diagnosis and especially in its predictive capacity; does unnecessary tests and treatment that drive up the costs of medicine. This revolution can go a long way in addressing these problems.
The potential of leveraging large amounts of data is fantastic. Through the ability to extract knowledge and learn from these data when combined with artificial intelligence and deep learning methods, we can achieve great precision in diagnosis and prognosis. With the help of these technologies, clinicians could increase their effectiveness and, above all, their efficiency in patient care, which is perhaps one of the great problems of current medicine.
Therefore, healthcare is a sector that would greatly benefit from AI. AI will save billions of euros in improving the prevention, diagnosis and treatment of problems such as childhood obesity, cardiovascular diseases and their sequelae, neurodegenerative diseases and breast cancer, among other areas. In addition, it will allow the development of new medicines and encourage personalized and home medicine or improve the quality of life of the elderly.
Personalized medicine has created a new paradigm where few doctors have the proper training. So, the professionals involved in the healthcare environment need to know himin the first place to face a very important change in the way of doing medicine. Secondly, the specific knowledge that will allow them to approach the generation and development of knowledge related to the technologies involved in this new paradigm. Lastly, they need the ability to create multidisciplinary teams that integrate professionals from the scientific and engineering environments to tackle the new challenges posed by this personalized medicine.
In this context, an AI capable of efficiently assisting medical professionals in their decisions and improving human-computer interaction methods is necessary. Doctors currently rely on clinical guidelines or experience. The guidelines may have the limitation of covering only part of the clinical practice and the experience of the biases associated with it. Automatic assistance, capable of performing these probability calculations in a normative manner and with real-time access to data from the electronic medical record, would allow for greater productivity for healthcare professionals. Training for the existence of a new generation of more technological doctors capable of helping in the design of these cognitive assistants is one of the challenges in this regard.
The so-called "P4 Medicine" (predictive, personalized, preventive, and participatory) will be based on emerging technologies such as AI and the analysis of large amounts of data based on machine learning and computer vision. Thus, data science will be routinely applied to structured and unstructured information from electronic health records, -omics (genomics, proteomics, transcriptomics, etc.) and medical imaging tools.
Thus, this specialization course is aimed at clinicians interested in knowing how AI is applied in health and how to do research with the data they have access to their jobs, medical records and other data collected by the services where they work. Generally these professionals are used to research using statistical techniques and now they want to go one step furthe
This revolution will also affect medicine. The same medicine is in a certain way in a moment of crisis. As a profession, despite the extraordinary advances in the art and science of medicine in the last four decades, it frequently presents limitations in diagnosis and especially in its predictive capacity; does unnecessary tests and treatment that drive up the costs of medicine. This revolution can go a long way in addressing these problems.
The potential of leveraging large amounts of data is fantastic. Through the ability to extract knowledge and learn from these data when combined with artificial intelligence and deep learning methods, we can achieve great precision in diagnosis and prognosis. With the help of these technologies, clinicians could increase their effectiveness and, above all, their efficiency in patient care, which is perhaps one of the great problems of current medicine.
Therefore, healthcare is a sector that would greatly benefit from AI. AI will save billions of euros in improving the prevention, diagnosis and treatment of problems such as childhood obesity, cardiovascular diseases and their sequelae, neurodegenerative diseases and breast cancer, among other areas. In addition, it will allow the development of new medicines and encourage personalized and home medicine or improve the quality of life of the elderly.
Personalized medicine has created a new paradigm where few doctors have the proper training. So, the professionals involved in the healthcare environment need to know himin the first place to face a very important change in the way of doing medicine. Secondly, the specific knowledge that will allow them to approach the generation and development of knowledge related to the technologies involved in this new paradigm. Lastly, they need the ability to create multidisciplinary teams that integrate professionals from the scientific and engineering environments to tackle the new challenges posed by this personalized medicine.
In this context, an AI capable of efficiently assisting medical professionals in their decisions and improving human-computer interaction methods is necessary. Doctors currently rely on clinical guidelines or experience. The guidelines may have the limitation of covering only part of the clinical practice and the experience of the biases associated with it. Automatic assistance, capable of performing these probability calculations in a normative manner and with real-time access to data from the electronic medical record, would allow for greater productivity for healthcare professionals. Training for the existence of a new generation of more technological doctors capable of helping in the design of these cognitive assistants is one of the challenges in this regard.
The so-called "P4 Medicine" (predictive, personalized, preventive, and participatory) will be based on emerging technologies such as AI and the analysis of large amounts of data based on machine learning and computer vision. Thus, data science will be routinely applied to structured and unstructured information from electronic health records, -omics (genomics, proteomics, transcriptomics, etc.) and medical imaging tools.
Thus, this specialization course is aimed at clinicians interested in knowing how AI is applied in health and how to do research with the data they have access to their jobs, medical records and other data collected by the services where they work. Generally these professionals are used to research using statistical techniques and now they want to go one step furthe
Scholarships and financial aid
Chek all the information on the possibilities for grants and scholarships in the page for UAB financial aids, grants and calls.
Coordinating centres
Instituto Universitario Fundación Parc Taulí
Departamento de Arquitectura de Computadores y Sistemas Operativos
Collaborating centres
Departamento de Ingeniería de la Información y de las Comunicaciones
Departamento de Microelectrónica y Sistemas Electrónicos
Departamento de Telecomunicación e Ingeniería de Sistemas
Departamento de Ciencias de la Computación
Contact
Secretaria técnica (efreixa@tauli.cat)
Phone: 937458238
Additional information
https://www.tauli.cat/es/institut/docencia/postgrau/inteligencia-artificial-en-salud/