{"id":20008,"date":"2025-01-08T16:17:29","date_gmt":"2025-01-08T20:17:29","guid":{"rendered":"https:\/\/ssaquebec.ca\/?p=20008"},"modified":"2026-08-06T16:16:52","modified_gmt":"2026-08-06T20:16:52","slug":"medomicslab-integrative-modeling-of-heterogeneous-data-in-medicine","status":"publish","type":"post","link":"https:\/\/ssaquebec.ca\/en\/news\/medomicslab-integrative-modeling-of-heterogeneous-data-in-medicine\/","title":{"rendered":"MEDomics: Developing AI-powered predictive models for personalized treatments"},"content":{"rendered":"\n<p class=\"wp-block-paragraph\"><strong>We envision the <a href=\"https:\/\/medomics.app\/\" target=\"_blank\" rel=\"noreferrer noopener\">MEDomics platform<\/a> becoming a powerful tool that strengthens collaboration among medical AI research teams.<\/strong> This collaborative platform for medical data modeling aims to develop predictive models for personalized treatments. MEDomics features analytical and machine learning capabilities and ultimately helps improve the quality of care provided to patients.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Indeed, MEDomics enables researchers\u2014whether they are clinicians or computer scientists\u2014to manage the entire lifecycle of a healthcare project (data, training, and evaluation) within a single interface. By combining <strong>a no-code and a code-based approach<\/strong>, the tool aims to rapidly transform complex clinical data into concrete predictive solutions to improve patient care. <strong>These individuals collaborate<\/strong> on defining the clinical problem, collecting data, managing data, generating AI hypotheses, refining hypotheses, and visualizing results.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">MEDomics addresses real-world needs:<\/p>\n\n\n<div class=\"wp-block-list\">\n<ul class=\"wp-block-list\">\n<li><strong>Tool fragmentation:<\/strong> The platform centralizes data management, training, and evaluation within a single workspace to avoid the need for multiple software applications.<\/li>\n\n\n\n<li><strong>Technical barriers<\/strong>: It enables non-programmer researchers to perform predictive modeling in medicine using a code-free graphical interface.<\/li>\n\n\n\n<li><strong>Collaborative synergy<\/strong>: It facilitates synergy between clinical and IT staff by converting visual workflows into editable Python code.<\/li>\n<\/ul>\n<\/div>\n\n\n<h2 class=\"wp-block-heading\">MEDomics Used in Teaching at McGill University<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">Here are some key milestones in the development of MEDomics. Since 2026, the platform has been used in medical physics courses at McGill University in Montreal.<\/p>\n\n\n<div class=\"wp-block-list\">\n<ul class=\"wp-block-list\">\n<li>First testing phase in early 2024: <a href=\"https:\/\/medomicslab.gitbook.io\/medomics-docs\/medomicslab-docs-v0\/test-with-mimic\">https:\/\/medomicslab.gitbook.io\/medomics-docs\/medomicslab-docs-v0\/test-with-mimic<\/a><\/li>\n\n\n\n<li>PREMs\/PROMS proof of concept in 2026: <a href=\"https:\/\/medomicslab.gitbook.io\/medomics-docs\/proofs-of-concept\/the-paris-demo\">https:\/\/medomicslab.gitbook.io\/medomics-docs\/proofs-of-concept\/the-paris-demo<\/a><\/li>\n\n\n\n<li>Use of MEDomics for teaching, Winter 2026, MDPH610 course at McGill:<a href=\"https:\/\/bit.ly\/4a7hMLM\"> mdph610_Syllabus_W2026.pdf<\/a><\/li>\n<\/ul>\n<\/div>\n\n\n<details class=\"wp-block-details is-layout-flow wp-block-details-is-layout-flow\"><summary>Key definitions<\/summary>\n<h4 class=\"wp-block-heading\">The name<\/h4>\n\n\n<div class=\"wp-block-list\">\n<ul class=\"wp-block-list\">\n<li>Data visualization<\/li>\n\n\n\n<li>MED = Heterogeneous Medical Data<\/li>\n\n\n\n<li>Omics = Characterization of biological processes<\/li>\n\n\n\n<li>Lab = Work platform<\/li>\n\n\n\n<li>Data integration<\/li>\n\n\n\n<li>Data pre-processing<\/li>\n\n\n\n<li>Data analysis<\/li>\n<\/ul>\n<\/div>\n\n\n<h4 class=\"wp-block-heading\">Graphical Pipeline (or Workflow)<\/h4>\n\n\n\n<p class=\"wp-block-paragraph\"><br>A graphical pipeline is a visual representation of a sequence of technical operations. Instead of writing lines of code to load an image, filter it, and then analyze it, the user connects functional \u201cnodes\u201d to one another on a canvas.<\/p>\n\n\n\n<h4 class=\"wp-block-heading\">Prediction Model (Medical AI)<\/h4>\n\n\n\n<p class=\"wp-block-paragraph\"><br>This model is an algorithm trained on medical data (text, images, or other) to identify complex patterns. Once validated, it can help diagnose a disease or estimate a patient\u2019s prognosis.<\/p>\n\n\n\n<h4 class=\"wp-block-heading\">Code generation<\/h4>\n\n\n\n<p class=\"wp-block-paragraph\"><br>Code generation is an automated process through which the platform translates a visual diagram (the graphical pipeline) into a structured programming language (Python).<\/p>\n<\/details>\n\n\n\n<div style=\"height:100px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<div class=\"wp-block-group\"><div class=\"wp-block-group__inner-container is-layout-constrained wp-block-group-is-layout-constrained\">\n<div class=\"wp-block-group\"><div class=\"wp-block-group__inner-container is-layout-constrained wp-block-group-is-layout-constrained\"><div class=\"block-accordion \">\n    <span class=\"block-accordion__label\">Accordion<\/span>\n    <h3 class=\"block-accordion__title\">Target audiences<\/h3>\n    \n<div class=\"wp-block-list\">\n<ul class=\"wp-block-list\">\n<li>Researchers<\/li>\n\n\n\n<li>Research professionals<\/li>\n\n\n\n<li>Healthcare professionals<\/li>\n<\/ul>\n<\/div>\n\n<\/div>\n\n                    \n\n\n<div class=\"block-accordion \">\n    <span class=\"block-accordion__label\">Accordion<\/span>\n    <h3 class=\"block-accordion__title\">Advantages<\/h3>\n    \n<div class=\"wp-block-list\">\n<ul class=\"wp-block-list\">\n<li><strong>Interdisciplinary synergy:<\/strong> enables clinical staff and IT specialists to collaborate more easily.<\/li>\n\n\n\n<li><strong>Democratization of medical AI:<\/strong> empowers healthcare professionals to independently lead complex research projects using a no-code interface.<\/li>\n\n\n\n<li><strong>Customization and reproducibility:<\/strong> ensures the quality and scientific rigor of results through an open-source, modular Python library that can be adapted to the specific needs of each project.<\/li>\n\n\n\n<li><strong>Model performance:<\/strong> facilitates the optimization of predictive algorithms by enabling a rapid transition between visual configurations and source code.<\/li>\n<\/ul>\n<\/div>\n\n<\/div>\n\n                    \n\n\n<div class=\"block-accordion \">\n    <span class=\"block-accordion__label\">Accordion<\/span>\n    <h3 class=\"block-accordion__title\">Key features or components<\/h3>\n    \n\n<p class=\"wp-block-paragraph\">Here are the features offered by the MEDomics platform:<\/p>\n\n\n<div class=\"wp-block-list\">\n<ul class=\"wp-block-list\">\n<li><strong>Visual pipelines <\/strong>for creating machine learning experiments.<\/li>\n\n\n\n<li><strong>Unified dashboard<\/strong>: a single interface for importing datasets, monitoring model training, and viewing performance metrics in real time.<\/li>\n\n\n\n<li><strong>Source code generation<\/strong>: export the visual pipeline to Python scripts (.ipynb).<\/li>\n\n\n\n<li><strong>Evaluation and interpretation of AI models.<\/strong><\/li>\n\n\n\n<li><strong>Deployment of AI models<\/strong> for application on new data.<\/li>\n<\/ul>\n<\/div>\n\n<\/div>\n\n                    \n\n\n<div class=\"block-accordion \">\n    <span class=\"block-accordion__label\">Accordion<\/span>\n    <h3 class=\"block-accordion__title\">Examples of use<\/h3>\n    \n\n<h3 class=\"wp-block-heading\">Case Study: Predicting and Managing Emotional Distress<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\"><br>A primary care team wants to identify patients experiencing emotional distress (anxiety, depression, irritability) using health questionnaires (PROMs\/ PREMs) in order to offer psychological support before their condition worsens.<\/p>\n\n\n\n<h4 class=\"wp-block-heading\"><strong>Using MEDomics:<\/strong><\/h4>\n\n\n<div class=\"wp-block-list\">\n<ul class=\"wp-block-list\">\n<li>Analysis of Determinants<div class=\"wp-block-list\">\n<ul class=\"wp-block-list\">\n<li>Staff use exploratory tools to correlate emotional distress with other factors in the patient\u2019s life, such as fatigue, chronic pain, or financial insecurity (difficulty paying for meals or rent).<\/li>\n<\/ul>\n<\/div><\/li>\n\n\n\n<li>Automatic identification<div class=\"wp-block-list\">\n<ul class=\"wp-block-list\">\n<li>Using the Learning Module, the platform trains a model that learns to identify at-risk patient profiles by combining their responses regarding vitality, sleep, and their sense of involvement in their care.<\/li>\n<\/ul>\n<\/div><\/li>\n\n\n\n<li>Clinical Validation<div class=\"wp-block-list\">\n<ul class=\"wp-block-list\">\n<li>Through the Evaluation Module, clinicians verify the reliability of predictions and identify which specific factors (e.g., a low sense of being treated as \u201ca whole person\u201d) most significantly contribute to mental distress.<\/li>\n<\/ul>\n<\/div><\/li>\n\n\n\n<li>Targeted Intervention<div class=\"wp-block-list\">\n<ul class=\"wp-block-list\">\n<li>The Application Module generates a prediction for each new completed questionnaire, alerting the team if a patient falls into the \u201cemotional distress\u201d category.<\/li>\n<\/ul>\n<\/div><\/li>\n<\/ul>\n<\/div>\n\n\n<h4 class=\"wp-block-heading\">Impact<\/h4>\n\n\n\n<p class=\"wp-block-paragraph\"><br>Patients benefit from a holistic and compassionate approach to their health. Early detection of distress allows for personalized care, facilitates discussions about emotional well-being during appointments, and enables patients to be quickly referred to appropriate social or psychological resources, thereby improving their overall quality of life.<\/p>\n\n\n<\/div>\n\n                    \n\n\n<div class=\"block-accordion \">\n    <span class=\"block-accordion__label\">Accordion<\/span>\n    <h3 class=\"block-accordion__title\">Team<\/h3>\n    \n\n<p class=\"wp-block-paragraph\">The MEDomics platform is developed by the MEDomicsLab research laboratory (medomicslab.com)<\/p>\n\n\n<\/div>\n\n                    \n\n\n<div class=\"block-accordion \">\n    <span class=\"block-accordion__label\">Accordion<\/span>\n    <h3 class=\"block-accordion__title\">To cite the tool<\/h3>\n    \n\n<p class=\"wp-block-paragraph\">MEDomicsLab. (s. d.).&nbsp;<em>MEDomics<\/em>.<br>https:\/\/medomics.app<\/p>\n\n\n<\/div>\n\n                    \n\n\n\n<h3 class=\"wp-block-heading\"><\/h3>\n<\/div><\/div>\n<\/div><\/div>\n\n\n\n<div class=\"wp-block-buttons is-layout-flex wp-block-buttons-is-layout-flex\">\n<div class=\"wp-block-button\"><a class=\"wp-block-button__link wp-element-button\" href=\"https:\/\/www.youtube.com\/watch?v=5eVyInq9N2I&amp;t=1s\">View video<\/a><\/div>\n\n\n\n<div class=\"wp-block-button\"><a class=\"wp-block-button__link wp-element-button\" href=\"https:\/\/medomics.app\/\" target=\"_blank\" rel=\"noreferrer noopener\">Visit MEDomics<\/a><\/div>\n<\/div>\n","protected":false},"excerpt":{"rendered":"<p>Developing predictive models for personalized treatments: that\u2019s what MEDomics makes possible. IT specialists are working with clinicians to improve patient care. Learn more.<\/p>\n","protected":false},"author":2,"featured_media":19608,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"_relevanssi_hide_post":"","_relevanssi_pin_for_all":"","_relevanssi_pin_keywords":"","_relevanssi_unpin_keywords":"","_relevanssi_related_keywords":"","_relevanssi_related_include_ids":"","_relevanssi_related_exclude_ids":"","_relevanssi_related_no_append":"","_relevanssi_related_not_related":"","_relevanssi_related_posts":"18102,10817,10895,10807,10728,10758","footnotes":""},"categories":[40],"tags":[],"article-type":[47,48],"class_list":["post-20008","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-uncategorized","article-type-deliverables","article-type-tools"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.8 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>MEDomics: Developing AI-powered 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