Our Approach
When it comes to innovation in healthcare, the limit of technology is always data; its quality, historical accuracy and size of the dataset. Thanks to the Zoī Check-Up, thousands of data points are collected, selected with care and structured, in a standardized and secure framework, with an exceptional level of quality.
By applying the latest AI and Machine Learning technologies to these data points, we aim to make innovative, personalized preventative medicine accessible to the greatest possible number of people. Research projects will be available on this page once initiated.
The Core Research Pillars at Zo ī
- 01
Diagnosis
We aim to predict an individual's overall health status using Machine Learning and multimodal AI models. Our mission goes beyond preventive medicine: We want to make predictive medicine accessible to all.
- 02
Personalization
Personalization is essential for prevention. We're developing a solution for healthcare professionals that enables them to propose optimal preventive care solutions, tailored to each of our members.
- 03
Impact
To maximize the acceptance and impact of health recommendations, we're working to identify the factors that contribute to good health and behavioral commitments. This methodology is crucial for scientifically demonstrating the positive impacts of a preventive approach on quality of life and the onset of disease.
Augmented Intelligence for Predictive Medicine
Together with our scientific and medical partners, we're building multimodal models that will help develop precision preventive medicine.
Our current research projects
Objectives
The aim of this study is to better understand the mechanisms of biological ageing using data collected during preventive health assessments performed at the Zoī Center. Researchers will apply established biological age algorithms to data from the Zoī cohort and will assess the added value of specific parameters collected by Zoī, such as oxidative stress markers, endocrine measurements, body composition, methylation markers, and health-related behaviours. This approach will: Identify biological and behavioural factors associated with ageing; Improve the accuracy of biological age prediction models; Explore the feasibility of developing an internal Zoī well-being / biological-age score for personalised prevention.
Members concerned
Only data from adult patients who underwent their preventive check-up between November 1, 2023, and April 10, 2025, will be included in the study.
Principal investigators
Dr. Jesse Poganik
Objectives
The aim of this study is to evaluate the potential value of a relatively unexplored imaging modality, the retro mode of the Mirante OCT system, in the analysis of retinal and choroidal pathologies. The study is based on a retrospective analysis of examinations already performed as part of preventive health assessments, with no impact on patient care. Researchers will compare images obtained in retro mode with other conventional imaging modalities to identify clinical situations in which this approach provides additional diagnostic value. The ultimate goal is to improve diagnostic accuracy and to optimise the use of advanced OCT imaging techniques within a preventive and personalised medicine framework.
Members concerned
Only data from adult participants who underwent a Mirante OCT examination including retro mode acquisition as part of a preventive health assessment between November 1, 2023 and May 22, 2025 will be included in the study.
Principal investigators
Dr. Sylvain Bodard, Ozlem Erol
Objectives
The aim of this study is to better understand a form of stress known as asymptomatic chronic stress. This is prolonged stress that can impact health, even if the individual does not feel it or show visible symptoms. To do so, researchers will retrospectively analyze data already collected during their preventive check-up, such as responses to stress questionnaires and certain biological test results. This will make it possible to identify different stress profiles in the population (for example: perceived stress with biological signs, or silent stress without subjective perception). The ultimate goal is to better detect this silent stress in order to develop more tailored and personalized prevention strategies.
Members concerned
Only data from adult patients who underwent their preventive check-up between November 1, 2023, and June 1, 2025, will be included in the study.
Principal investigators
Dr. Marie Bringer
Objectives
The objective of this study is to characterize the risk of cognitive decline in the Zoī cohort using validated tools from the scientific literature. This analysis will not only allow discussion of the relevance of these tools but also help identify specific risk and protective factors within the Zoī cohort.
Members concerned
Only data from adult patients who underwent their preventive check-up between November 1, 2023, and June 1, 2025, will be included in the study.
Principal investigators
Dr. Adrien Julian (Neurologist)
Objectives
This study aims to describe the distribution of blood pressure levels in a primary prevention population and to assess the impact of the new European Society of Cardiology (ESC 2024) recommendations on blood pressure classification.
Members concerned
Only data from adult patients (18 years and older) who underwent their preventive check-up between November 1, 2023, and May 22, 2025, are included in this study.
Principal investigators
Dr. Sylvain Bodard
Objectives
The aim of this study is to evaluate the usefulness of thoracic ConeBeam CT (latest generation) for detecting cardiovascular risk factors such as aortic and coronary calcifications, as well as other relevant cardiovascular indicators (aortic diameter, cardiomegaly—i.e. enlarged heart size).
Members concerned
Only data from adult patients who underwent a thoracic CBCT as part of their preventive check-up between November 1, 2024, and May 22, 2025, are included in this study.
Principal investigators
Dr. Léo Mabit (Radiologist)
Objectives
The main objective of this cohort study is to describe the population and data structure of Zoī members, and to provide information on preventive and predictive health through the analysis of pseudonymized real-world data. The study will offer a descriptive overview of key health indicators, such as the prevalence of chronic diseases (e.g. hypertension, diabetes, dyslipidemias), lifestyle behaviors, healthcare utilization and adherence to prevention strategies within the cohort.
Members concerned
The data already collected concerns members who have completed the Prevention Check-Up since November 2023. Data from members who complete their Prevention Check-up from December 2024 onwards will then be collected as the study progresses.
Principal investigators
Objectives
The aim of the study is to assess the value of using ConeBeam or cone-beam computed tomography (CBCT) for thoracic imaging in preventive medicine. The results of this feasibility study will lay the foundations for future research and clinical validation of CBCT as a low-radiation alternative for thoracic imaging.
Members concerned
The data that will be used for the study comes in particular from the completion of the Prevention Check-Up and the use of the Services and from the Application of members who smoke, members over 60 years of age, members with a family history of lung cancer, or members with a pulmonary symptomatology indicating the performance of a thoracic imaging having performed a CBCT examination (as part of their Prevention Check-up) between the months of November 2023 and April 2025.
Principal investigators
Dr. Sylvain Bodard
Objectives
Develop and evaluate the performance of Zoī recommendation models, with the aim of improving the quality of medical practices in the field of preventive medicine
Members concerned
Zoī’s Members who have completed their Prevention Check-up from November 2023 onwards
Principal investigators
Dr. Pierre Bauvin
Collaborate with Zoī
Are you passionate about these areas of research and have ideas to change the future? Join the Zoī research team.