Resources

Through articles and studies, the Kaduceo team shares its knowledge in data science applied to the health sector

Coalitional Strategies for Efficient Individual Prediction Explanation

Coalitional Strategies for Efficient Individual Prediction Explanation

As machine learning (ML) is now widely applied in many fields, understanding what happens inside the black box is becoming a growing demand, especially by non-experts of these models.

Trends in metabolic bariatric surgery in adolescents in France

Trends in metabolic bariatric surgery in adolescents in France

This study analyzes trends in metabolic bariatric surgery among adolescents in France on the basis of national data over an 11-year period

Comparison of Surgical Activity and Scientific Publications in Bariatric Surgery

Comparison of Surgical Activity and Scientific Publications in Bariatric Surgery

In particular, this study reveals many similarities in the pattern of publications and procedures in bariatric surgery

Impact of COVID-19 on surgical emergencies: nationwide analysis

Impact of COVID-19 on surgical emergencies: nationwide analysis

To cope with the burden of disease, hospital staff were reassigned and elective surgery was significantly delayed. Various countries implemented national containment […].

Prediction of unplanned readmissions

Prediction of unplanned readmissions

Following initial hospitalization, re-admissions for pulmonary pathologies are among the conditions that generate the most readmission and consequently lead to additional expenditure on social security.

State of art: Explainability of AI models

State of art: Explainability of AI models

To reduce errors and better understand the predictions made by AI, the explicability of AI models (XAI for "eXplainable AI") has emerged as a research field.

Medical imaging: Explainability methods for image classification

Medical imaging: Explainability methods for image classification

Automatic image analysis has seen its performance grow strongly in recent years. These recent advances improve the construction of predictive imaging models, increasing their reliability

Healthcare journey

Healthcare journey

Our journey design begins with the first recording of a patient for a reason in a healthcare facility until the last event of their management: Time sequence of all care

State of the art: Prediction of hospital readmission

State of the art: Prediction of hospital readmission

The study of hospital readmission could contribute to the improvement of care paths but the subject is quite complex. The different models in the literature are difficult to compare. To

Covid-19 : Predicting admissions and extracting valuable insights from data analytics

Covid-19 : Predicting admissions and extracting valuable insights from data analytics

Faced with this health crisis, it was natural for Kaduceo to make our expertise available to hospitals. Adapting some of our predictive and indicator models to allow hospitals to have

Neural Network Architectures for image classification

Neural Network Architectures for image classification

From examples where each image is associated with a category, the so-called Machine Learning models learn to identify patterns specific to the observations of the same category, with the aim

Lung Cancer : How to predict an early death ?

Lung Cancer : How to predict an early death ?

Lung Cancer: Analyze the profile and health care facility transitions of patients with lung cancer to infer elements that characterize early death

Emergency Activity Prediction AI Model

Emergency Activity Prediction AI Model

The main challenge is to be able to provide forecasts that are reliable enough to alert hospitals in the event of a peak of activity. We are looking to propose

An idea ? A project ?

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