The Future of Digital Healthcare with Federated Learning
In an era where data is considered the new oil, the need for effective and secure data processing methods has never been more critical. Traditional centralized data processing methods, aggregating data in a central server for analysis and machine learning, present significant privacy and security challenges. This is where federated learning comes into play. Federated […]
From Real World Data (RWD) towards Real World Evidences (RWE)
Per the definition by the US FDA, real-world data (RWD) in the medical and healthcare field “are the data relating to patient health status and/or the delivery of health care routinely collected from a variety of sources”[1]. The wide usage of the internet, social media, wearable devices and mobile devices, claims and billing activities, (disease) […]
Steering the future in the right direction: introducing the new European AI office
The European AI Office, established within the European Commission, is dedicated to supporting the development and use of trustworthy AI while mitigating AI risks. It serves as the center of AI expertise and lays the groundwork for a unified European AI governance system. The AI Act, a comprehensive legal framework on AI, ensures safety, trustworthiness, […]
Federated learning applied to multicenter clinical studies: why it can change the world?
Multicenter clinical studies play a pivotal role in medical research, but the traditional approach of centralizing data analysis poses significant challenges. From privacy concerns to logistical bottlenecks, these hurdles hinder progress. Federated learning emerges as a game-changer, offering a decentralized solution that not only addresses these challenges but also has the potential to redefine global […]
Breaking grounds in healthcare: TRUMPET consortium meeting and dissemination event in Cesena
In a pivotal step toward advancing data-driven healthcare, the TRUMPET project recently hosted a consortium meeting in Cesena, Italy, accompanied by an insightful healthcare conference. The project is a groundbreaking initiative funded under the Horizon Europe framework, aimed at revolutionizing clinical data analysis through state-of-the-art federated AI solutions. A successfully TRUMPET consortium meeting held in […]
Trustworthy AI, tooling up the methods: register for the upcoming TRUMPET Exchange Talks
A new opportunity to get inside the topic of TRUMPET project, gaining useful insight for Federated Learning application in healthcare. On December, 4th, Dr. Zakaria Chihani, from CEA will held a seminar titled ” Trustworthy AI, tooling up the methods”. REGISTER TO THE WEBINAR AI model: ensuring trustworthiness is a focal point In the ever-evolving […]
From cryptography over statistics and medicine: the need for multi-disciplinary collaboration
Over many centuries, medical science has accumulated a vast and profound knowledge of the human body and how treatments can heal diseases. However, some biological processes are too complex to fully understand, describe in a text book or study manually. Moreover, each patient is different, e.g., because he has different genes, lives in a different […]
TRUMPET exchange Talks: workshop on GDPR
TRUMPET exchange Talks: workshop on GDPR In today’s digital age, data protection and privacy are paramount, especially in the field of healthcare research. To shed light on this critical topic, we invite you to join our upcoming virtual workshop: “Workshop on GDPR for Ensuring Health Data Privacy in Research.” Understanding GDPR in healthcare The General […]
Differential privacy in Federated Learning: balancing privacy and utility
In recent years, the use of Artificial Intelligence (AI) has seen a significant surge in everyday applications. Part of this technology relies on Machine Learning algorithms that gather data to train analytical and AI models. However, in many instances, this data is stored in different repositories with certain limitations on data sharing. To address this, […]
Uses and application of Privacy Enhancing Technologies
Privacy Enhancing Technologies, also known as PETs, encompass a diverse range of tools aimed at maximizing the protection of individuals’ privacy. According to the European Union Agency for Cybersecurity (ENISA), PETs are defined as[1] “software and hardware solutions, i.e. systems encompassing technical processes, methods or knowledge to achieve specific privacy or data protection functionality or […]