Showing 136-140 of 258 resources:
How’d They Do It? Tech Leaders Reflect on How They Innovated To Solve Health Problems

Built In Publish Date: September 9, 2022 Read the Full Article >> About the company: Founded in 2015, OM1 developed its data cloud to provide advanced technological tools for researchers and support their quest to find new ways of understanding and treating chronic conditions. Yaning Zhang, Sr. Software Engineer, shared how OM1 turns data into insight:[…]

Using Real-World Data for Patients with Multiple Sclerosis: A New Machine Learning Model for the Expanded Disability Status Scale (EDSS)

HealthEconomics.com – A Scientist.com Company Publish Date: August 26th, 2022   Multiple sclerosis (MS) is a chronic illness in which the body’s immune system attacks myelin, the substance that surrounds and protects the nerve fibers of the central nervous system. The result is a disabling disease that causes damage to the brain and spinal cord[…]

AI Applications for Clinical Development: From Identifying Patients to Amplifying Trial Endpoints

Inside Precision Medicine Published Online: August 18, 2022 Read the Full Article >> Artificial intelligence (AI) has promised major breakthroughs in clinical development success. While the hype has sometimes seemed overblown, AI is starting to deliver on those promises through real-world impact. AI is not a silver bullet for all challenges, but in specific applications,[…]

Using Real-World Data to Unlock Better Outcomes in IBD & NASH Patients

Gastrointestinal and metabolic disorders are highly prevalent and result in reduced quality of life for many patients. Treatments are aimed at reducing symptoms and preventing complications and progression. More research is needed to better understand natural history and progression, treatment effectiveness, and outcomes. Register here Linked real-world data (RWD) and machine learning (ML) applications provide[…]

Finding hard-to-find patients: Integrating real-world data and AI

BioPharma Dive Published Online: July 18, 2022 Read the Full Article>> Identifying patients ‘outside the clinic’ can provide significant benefits for researchers and population health managers. Better understanding of patient cohorts can shed light on patient journeys, help optimize decisions around treatment choice and timing and inform the development of new therapies and intervention programs.[…]