Microsoft signs a collaboration agreement with CiTIUS for research in Artificial Intelligence applied to medicine
The technology multinational has reached an agreement with the center for the application of AI in medicine, particularly in the field of oncohematology.
CiTIUS has just received support from Microsoft for the development of new Artificial Intelligence (AI) techniques applied to medicine. In particular, this new line of collaboration will focus on the field of oncohematology, a discipline centered on the treatment of tumors that originate in the organs responsible for forming blood and in the lymph nodes (including leukaemias, lymphomas and multiple myeloma). This is a line of research currently active at the USC research center, under a recent agreement between CiTIUS and the Health Research Institute of Santiago de Compostela (IDIS).
Microsoft’s support will make it possible to achieve different milestones in this field of research: on the one hand, machine learning techniques will be applied for better prediction of survival and optimization of the treatment of patients with multiple myeloma; on the other hand, a specific two-day event will be organized to analyse, in a more general way, the use of Artificial Intelligence in Medicine.
The first of these days will begin with an introduction to the fundamentals of Artificial Intelligence and some of its applications in medicine, presenting concrete cases of knowledge-based and machine learning systems (including the use of Artificial Intelligence in the fight against COVID-19). On the second day, practical aspects related to privacy and ethics in the application of AI in the medical field will be addressed, as well as the use of language technologies: from the analysis and generation of texts to interaction and explainability. In addition, this second day will also present several applications of Artificial Intelligence in medical imaging and in signal processing in general. Finally, the level of development achieved by some tools and utilities that have moved from the laboratory to the market will be shown, including the case of personalized medicine in oncohematology.
Trustworthy Artificial Intelligence
In parallel, another of the activities planned under this new collaboration agreement will be a debate day on the European Commission’s legislative proposal for the drafting of an Artificial Intelligence Act, whose draft was published on 21 April 2021. The main objective of this day will be to present, discuss and contribute ideas on the proposed law to regulate AI (especially in the areas of trustworthy and explainable AI), bringing together a plurality of viewpoints. The event will be held as part of the NL4XAI - Interactive Natural Language Technology for Explainable Artificial Intelligence project, the European Training Network for new PhD students under the Marie Sklodovska-Curie Actions programme, led by CiTIUS within the prestigious European Horizon 2020 programme, and will feature representatives from universities, companies, public administrations and social stakeholders.
Improving therapies through the use of intelligent technologies
Oncohematology is a discipline focused on the treatment of bone marrow cancer, including leukaemia, lymphomas and multiple myeloma. Advances in the understanding of these diseases have made it possible to generate a large amount of clinical and biological data, accompanied by constant pharmacological innovation, including the incorporation of increasingly specific and effective drugs with fewer adverse effects. Current medical practice is increasingly based on scientific evidence, but due to the extreme complexity of many processes and budgetary constraints on the development of clinical trials and biological studies, much real-world practice continues to rely on personal experience or indirect data. This is especially important in oncohematology, where diseases such as acute leukaemia, lymphoma or multiple myeloma are treated using a therapeutic approach based on estimated risk. In some cases this is done in a rather rudimentary way, while in others a "one-size-fits-all" approach is adopted, where almost all patients receive standard treatments. This new research aims to improve therapeutic management by applying specific protocols adapted to patient risk and/or directly selecting the type of therapy that maximizes each individual’s chances of survival.
Investing in technologies for health
In 2016, AI projects in the health field attracted more investment than AI projects in any other sector of the global economy. The real challenge of this innovative approach is to bring medical practice even closer to the patient, making healthcare "more human" with the help of machines, which can make it more efficient and effective. Some examples of this are the development of personalized treatments or the automation of the capture, organization and processing of the vast amount of medical data and information.
CiTIUS has just received support from Microsoft for the development of new Artificial Intelligence (AI) techniques applied to medicine. In particular, this new line of collaboration will focus on the field of oncohematology, a discipline centered on the treatment of tumors that originate in the organs responsible for forming blood and in the lymph nodes (including leukaemias, lymphomas and multiple myeloma). This is a line of research currently active at the USC research center, under a recent agreement between CiTIUS and the Health Research Institute of Santiago de Compostela (IDIS).
Microsoft’s support will make it possible to achieve different milestones in this field of research: on the one hand, machine learning techniques will be applied for better prediction of survival and optimization of the treatment of patients with multiple myeloma; on the other hand, a specific two-day event will be organized to analyse, in a more general way, the use of Artificial Intelligence in Medicine.
The first of these days will begin with an introduction to the fundamentals of Artificial Intelligence and some of its applications in medicine, presenting concrete cases of knowledge-based and machine learning systems (including the use of Artificial Intelligence in the fight against COVID-19). On the second day, practical aspects related to privacy and ethics in the application of AI in the medical field will be addressed, as well as the use of language technologies: from the analysis and generation of texts to interaction and explainability. In addition, this second day will also present several applications of Artificial Intelligence in medical imaging and in signal processing in general. Finally, the level of development achieved by some tools and utilities that have moved from the laboratory to the market will be shown, including the case of personalized medicine in oncohematology.
Trustworthy Artificial Intelligence
In parallel, another of the activities planned under this new collaboration agreement will be a debate day on the European Commission’s legislative proposal for the drafting of an Artificial Intelligence Act, whose draft was published on 21 April 2021. The main objective of this day will be to present, discuss and contribute ideas on the proposed law to regulate AI (especially in the areas of trustworthy and explainable AI), bringing together a plurality of viewpoints. The event will be held as part of the NL4XAI - Interactive Natural Language Technology for Explainable Artificial Intelligence project, the European Training Network for new PhD students under the Marie Sklodovska-Curie Actions programme, led by CiTIUS within the prestigious European Horizon 2020 programme, and will feature representatives from universities, companies, public administrations and social stakeholders.
Improving therapies through the use of intelligent technologies
Oncohematology is a discipline focused on the treatment of bone marrow cancer, including leukaemia, lymphomas and multiple myeloma. Advances in the understanding of these diseases have made it possible to generate a large amount of clinical and biological data, accompanied by constant pharmacological innovation, including the incorporation of increasingly specific and effective drugs with fewer adverse effects. Current medical practice is increasingly based on scientific evidence, but due to the extreme complexity of many processes and budgetary constraints on the development of clinical trials and biological studies, much real-world practice continues to rely on personal experience or indirect data. This is especially important in oncohematology, where diseases such as acute leukaemia, lymphoma or multiple myeloma are treated using a therapeutic approach based on estimated risk. In some cases this is done in a rather rudimentary way, while in others a "one-size-fits-all" approach is adopted, where almost all patients receive standard treatments. This new research aims to improve therapeutic management by applying specific protocols adapted to patient risk and/or directly selecting the type of therapy that maximizes each individual’s chances of survival.
Investing in technologies for health
In 2016, AI projects in the health field attracted more investment than AI projects in any other sector of the global economy. The real challenge of this innovative approach is to bring medical practice even closer to the patient, making healthcare "more human" with the help of machines, which can make it more efficient and effective. Some examples of this are the development of personalized treatments or the automation of the capture, organization and processing of the vast amount of medical data and information.