RELEVIUM
For Researchers and Clinicians
Interesting links, articles, studies, projects, and content for researchers and clinicians in the field
Our research goals
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Develop an AI-based Decision Support System (AI-DSS) for Pancreatic Ductal Adenocarcinoma (PDAC) to assist healthcare professionals in making better treatment decisions
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Create a comprehensive dashboard for clinicians, patients, and caregivers, providing valuable information for improved disease management and treatment choices
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Develop guidelines for supportive and palliative care specific to PDAC, providing evidence-based recommendations for healthcare professionals and improving patient outcomes
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02
Enhance data collection and analysis capabilities through user-friendly mobile applications for PDAC patients, caregivers, and clinicians
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Build estimation models for neuropathic pain and sarcopenia to aid in accurate assessment and personalized care for PDAC patients
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10
Develop causal models for assessing the effectiveness of pain management strategies and nutritional/physical activity interventions, aiding in evidence-based decision-making and improving patient care
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Design a wearable device to monitor and manage pain in real-time for PDAC patients
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Create an early cachexia estimation model to identify and intervene in cachexia cases at an early stage, improving patient outcomes
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04
Develop a monitoring tool for assessing sarcopenia in PDAC patients to aid in early detection and intervention
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08
Investigate and develop multi-modal interventions to enhance the quality of life (QoL) for PDAC patients, focusing on diverse aspects such as pain management, nutrition, and physical activity
Our solution
In the Relevium project, we utilize a range of sensor data, such as heart rate variability, electrodermal activity, and pain sensation, collected through sensors and an app. These data serve as valuable input for both developing medical models and designing effective interventions.
By analyzing the data, we derive causal models that enable us to predict disease progression and identify potential improvements that can be achieved through lifestyle changes. This data-driven approach helps us understand the underlying factors influencing health outcomes.
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When planning interventions for patients, we employ Explainable Artificial Intelligence (AI) techniques to analyze the current health data in accordance with these models. This allows us to provide transparent and understandable insights into the analysis results. Our focus is on ensuring the ethical use of these results for intervention planning.
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Equipped with these explainable analysis outcomes, healthcare professionals can make informed decisions when creating personalized lifestyle interventions for patients. We prioritize the comprehensibility of the analysis results, enabling professionals to effectively communicate and collaborate with patients in their treatment journey.
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Through the combination of causal medical models and Explainable AI, the Relevium project aims to provide actionable insights for intervention planning, empowering patients and healthcare professionals to make informed decisions and improve patient outcomes.
Relevant research, publications and studies
KITTU
KITTU aims to develop an AI system in urology that assists physicians and patients in decision-making by providing comprehensive options. It relieves the burden on individuals involved and optimizes therapy decisions, contributing to healthcare optimization. Integration into the digitalization of the healthcare system involves interdisciplinary collaboration. The goal is to improve evidence-based treatment recommendations in oncology, reducing side effects and enhancing quality of life. KITTU plans to expand beyond urology, making a significant impact on cancer care.
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The Cancer Survivorship - AI for Well-being cluster (#CS_AIW) unites various EU-funded projects focused on Artificial Intelligence (AI) for healthcare and well-being within the Cancer Survivorship domain. The cluster emphasizes collaboration, rejecting siloed approaches to foster an ethos of cross-fertilization. Members engage in activities like patient association involvement, roundtable discussions, workshops, podcasts, and the development of common data in post-cancer treatment. This collaborative initiative has proven highly beneficial, enhancing cross-sector collaboration, sharing best practices, and reaching a broader audience. The cluster's evolution demonstrates its success in generating, activating, and communicating knowledge and innovation in mental health, well-being, cancer recovery, patient support, and participatory research.
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Quality of Life EU- Cluster organized a meeting on the topic of "Health Economic analyses across Europe", where the RELEVIUM project was presented.
EORTC
EORTC's GI clinical research explores genetic, epigenetic, and immunologic factors in gastrointestinal tumors. Their trials bridge preclinical and clinical stages, investigating new aspects of tumor biology using advanced technology. With a patient-centered approach, their mission is to develop innovative therapeutic strategies through multidisciplinary studies. They collaborate with diverse cancer research networks, enrich their expert team, and empower future leaders in GI cancer research.
European Health and Digital Executive Agency
In the ongoing European Week Against Cancer, the EU underscores its commitment to cancer research and innovation. Highlighting projects funded by the Horizon 2020 programme, the focus is on leveraging artificial intelligence (AI) to enhance cancer treatment. Initiatives like QUALITOP aim to create an open digital platform for immunotherapy, while ASCAPE develops an AI infrastructure for hospitals, prioritizing breast and prostate cancer. PANCAIM utilizes AI to integrate genomics and imaging phenomics for personalized pancreatic cancer medicine, and CLARIFY focuses on predicting post-treatment health status for cancer survivors through big data and AI techniques. These endeavors collectively aim to advance personalized medicine, improve treatment outcomes, and enhance the quality of life for cancer survivors.
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The PANCAID project is an international research consortium focused on advancing early detection of pancreatic cancer through a minimally invasive blood test. By analyzing genetic mutations, circulating tumor cells, and other biomarkers, the project aims to detect pancreatic cancer at earlier stages, potentially revolutionizing current diagnostic methods. Involving 17 partners from eight countries, PANCAID brings together expertise in oncology, molecular biology, bioinformatics, and clinical research. With a five-year funding period starting in January 2023, the project seeks to make significant progress in early detection, treatment, and ultimately improving patient outcomes.