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Dermatology Data Can Direct Policy Priorities, but Gaps Reflect Inequities of Care

American Journal of Managed Care Mar 17, 2023 Christina Mattina Read the Full Article >> Speakers at the American Academy of Dermatology 2023 Annual Meeting highlighted the potential of DataDerm to tell the story of dermatological care in the United States, but some also cautioned that the registry only reflects those who have access to[…]

Hard to Define, Harder to Find Patients: Using AI & Real-World Data to Understand Treatment Resistant Depression

Published March 13, 2023 from Read the full article >> Mental health conditions can take a staggering toll on an individual physically, socially and financially. Many patients languish with partially effective or ineffective treatments, even though new options are constantly entering the market. At OM1, we are using our extensive mental health data network[…]

AI Uncovers Other Patients Like You to Support Doctors with ChatGPT

Watch the full interview from Healthcare IT about ChatGPT for un-diagnosed patients with Joseph Zabinski, PhD, Senior Director, AI & Personalized Medicine at OM1. The road to diagnosis can be taxing for patients and once diagnosed, personalized treatment plans are still created with an element of guess work. Automation and artificial intelligence (AI) are the[…]

Validation of a machine learning approach to estimate expanded disability status scale scores for multiple sclerosis

Published: June 22, 2022 Sage Journals Read the Full Article >> Background: Disability assessment using the Expanded Disability Status Scale (EDSS) is important to inform treatment decisions and monitor the progression of multiple sclerosis. Yet, EDSS scores are documented infrequently in electronic medical records. Objective: To validate a machine learning model to estimate EDSS scores[…]

Validation of a machine learning approach to estimate Clinical Disease Activity Index Scores for rheumatoid arthritis

Published: October 29, 2021 Read the Full Article >> Objective: Disease activity measures, such as the Clinical Disease Activity Index (CDAI), are important tools for informing treatment decisions and monitoring patient outcomes in rheumatoid arthritis (RA). Yet, documentation of CDAI scores in electronic medical records and other real-world data sources is inconsistent, making it challenging[…]

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