Showing 1-5 of 54 webinars:
Practical AI: Adding Insight to the Patient Journey with Digital Phenotyping

DATE: Thursday, May 23, 2024 TIME: 11:00 am EST PRESENTER: Joseph Zabinski, PhD REGISTER HERE >> In this webinar, Dr. Joseph Zabinski will discuss the digital phenotyping process and several concrete applications to demonstrate how AI can add value to analyses of the patient journey across the life sciences spectrum. Real-world data provide insight into[…]

Integrated Evidence Generation: Exploring Registries in the Era of Automation

Thu, Mar 28, 2024 2:00 PM – 3:00 PM EDT Presenters: Sonja Wustrack, MPH, Managing Director, Integrated Evidence Generation and Michelle Leavy, MPH Director, Real-World Evidence Strategy Register >> Integrated evidence generation is gaining traction in the biopharmaceutical industry as an approach to aligning evidence needs across functions within a company. Real-world data and real-world[…]

AI and Digital Phenotyping for Clinical Development

Wed, Jan 31, 2024 2:00 PM – 3:00 PM EST Register here >> With the new year comes even more hype with how AI will transform the healthcare and pharmaceutical landscape – including McKinsey estimating that AI technology could generate up to $110 billion a year in economic value for the pharma and medical-product industries.[…]

Shifting the Paradigm (and Prince)on Integrated Evidence Generation

MAPS Webinar 9/15/23 Listen to the full webianr >> Clinical research is typically costly for sponsors and burdensome for providers and patients. New methods and approaches, such as integrated evidence generation using real-world data networks and automated study platforms, are accelerating the path from start-up to read out.

Improving Patient Outcomes: AI-Based Phenotyping for Diagnosis, Treatment, and Clinical Trials

Register to watch>> Join a panel of OM1’s clinical experts in cardiometabolic disease, immunology, and mental health as they explore how Artificial Intelligence (AI) can find phenotypic patterns and unlock insights hidden in real-world data. Extracting as much information as possible from real-world datasets is essential for understanding the complete patient journey. Subtle patterns in[…]

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