Case StudyAIMental HealthBringing Treatment-Resistant Depression to Light: AI-Driven Patient Discovery in Real-World DataRead more
PublicationAIMental HealthAI-Based Estimation of the CGI-I to Address Gaps in Real-World Data and Increase Study Sample SizeDownload
PublicationDataMental HealthSuicidal Ideation in Patients Treated with Glucagon-like Peptide 1 Receptor (GLP1) Agonists: A Retrospective Real-World AnalysisDownload
PublicationDataMental Healthhe Association Between Adherence to Esketamine Nasal Spray Therapy Dosing Regimen and Changes in Depressive Symptoms Among Patients With Treatment-Resistant Depression in the U.S.Download
PublicationDataMental HealthAddressing Gaps in Real-World Data Sources through Automated Extraction of Psychiatric Comorbidities and Medication Side Effects from Clinical NotesDownload
PublicationAIMental HealthIdentification of Treatment Resistant Major Depressive Disorder using a Machine Learning AlgorithmDownload
PublicationAIMental HealthUse of Medical Language Processing in Real-World Data to Understand Antidepressant Side Effects and Improve Research in Mental HealthDownload
PublicationAIMental HealthDevelopment of a Machine Learning Model for Estimating PHQ-9 Scores Using Clinical Notes from Real-World Data SourcesDownload
PublicationAIMental HealthThe Association Between Credit Risk Score and Major Depressive Disorder Burden Using a Machine Learning Estimation of the PHQ-9 in a Real-World CohortDownload
PublicationDataMental HealthThe Association Between Race, Social Determinants of Health, and Treatment for Major Depressive Disorder (MDD) in a Real-World CohortDownload
PublicationDataMental HealthChanges in Weight Across the Life Span in Patients with Bipolar Disorder I Treated with Second Generation AntipsychoticsDownload
PublicationAIMental HealthUse of a Natural Language Processing-Based Approach to Extract Depression Symptom Severity and Suicide Ideation from Clinical Notes to Support Depression ResearchDownload
PublicationDataMental HealthWeight Gain and Treatment Interruptions With Second-Generation Oral Antipsychotics: Analysis of Real-World Data Among Patients With Schizophrenia or Bipolar I DisorderDownload
PublicationDataMental HealthEvaluating the Feasibility of Capturing a Core Set of Harmonized Depression Outcome Measures in Primary Care and Mental Health Patient RegistriesDownload
PublicationDataMental HealthDepression and Patient Outcomes Among Rheumatoid Arthritis Patients in a Large US-Based Real World CohortDownload
PublicationDataMental HealthPatient & Provider Characteristics Associated with PHQ-9 Administration and Outcomes Assessment in Routine Clinical Practice: Findings from the OM1 Intelligent Data CloudDownload
PublicationAIMental HealthDevelopment of a Machine Learning Model for Estimating CGI-I Scores Using Electronic Medical Records from Real-World Data Sources in Schizophrenia, Bipolar I and Major Depressive DisorderDownload
PublicationDataMental HealthReductions in Depressive Symptoms After Brexpiprazole Augmentation Among Patients with Major Depressive Disorder Receiving Antidepressant Therapy in Real-World SettingsDownload
PublicationDataMental HealthHarmonized Outcome Measures for Use in Depression Patient Registries and Clinical PracticesDownload
PublicationDataMental HealthClinical burden of major depressive disorder with versus without prominent anhedonia using a real-world electronic health records and claims linked databaseDownload
PublicationDataMental HealthReal-world effectiveness of cariprazine in major depressive disorder and bipolar I disorder in the United StatesRead more
PublicationAIMental HealthA machine learning model using clinical notes to estimate PHQ-9 symptom severity scores in depressed patientsDownload
PublicationDataMental HealthWeight Gain and Comorbidities Associated With Oral Second-Generation Antipsychotics: Analysis of Real-World Data for Patients With Bipolar I Disorder or SchizophreniaDownload
Webinar & VideoAIMental HealthPredicting Response and Personalizing Treatment Decisions in Mental Health: New Opportunities with AI and Real-World DataRead more
Webinar & VideoAICardioMental HealthBehind the Insights: Ep 04 GLP-1s & Suicidal Ideation, Jessica Probst, MPH & Carl Marci, MDRead more
News & ArticleAIMental HealthUnderstanding the link between GLP-1 therapies and suicidal ideation using real-world dataRead more
News & ArticleDataCardioMental HealthOM1 to Present Groundbreaking Research on GLP-1 Agonists and Suicidal Ideation at ISPOR 2025.Read more
News & ArticleDataMental HealthOM1 to Present Groundbreaking Research on GLP-1 Agonists and Suicidal Ideation at ISPOR 2025Read more
News & ArticleDataMental HealthOM1 expands mental health network to over six million patients, enhancing real-world evidence and personalized care capabilitiesRead more
News & ArticleDataMental HealthOM1 Adds 1 Million Patients to Its Mental Health Network, Significantly Expanding Specialty Coverage and Driving New Possibilities for Real-World Research and Personalized CareRead more
Webinar & VideoAIMental HealthBehind the Insights: Ep 03 Decoding Treatment-Resistant Depression with Carl Marci, MDRead more
News & ArticleDataMental HealthMDMA Therapy for Mental Health Conditions: Do the Benefits Outweigh the Risks?Read more
News & ArticleAIMental HealthPeople are using ChatGPT as a therapist. Mental health experts have some concernsRead more
Webinar & VideoAIMental HealthUnveiling the Unseen: AI's Role in Identifying Treatment-Resistant DepressionRead more
News & ArticleAIMental HealthIntegrating Ambient Clinical Voice Technology – The Impacts, Challenges, and BenefitsRead more
News & ArticleDataMental HealthEXPERT PRAISES PROPOSED FEDERAL RULE TO STRENGTHEN BEHAVIORAL HEALTH PARITYRead more
News & ArticleAIMental HealthMachine learning model accurately estimates PHQ-9 scores from clinical notesRead more
News & ArticleDataMental HealthHow Real-World Data Can Contribute to Improved Mental Health TreatmentRead more
News & ArticleAIMental Health“I Know It When I See It”: Definitions of Treatment-Resistant DepressionRead more
News & ArticleDataMental HealthOM1 Launches Analytics to Deliver Mental Health & Immunology Insights on Prescriber Trends and Therapy EffectivenessRead more
News & ArticleAIMental HealthAs suicide rates spike, new AI platform could ‘fill the gap’ in mental health care, say Boston researchersRead more
News & ArticleAIMental HealthHard to Define, Harder to Find Patients: Using AI & Real-World Data to Understand Treatment Resistant DepressionRead more
News & ArticleDataMental HealthOM1 Expands Mental Health Offering With Real-World Datasets Including Schizophrenia and Bipolar DisorderRead more
News & ArticleDataMental HealthReal-World Data Delivers Dose of Hope for Mental Health in the U.S.Read more
![MIAMI BEACH, Fla. — A novel machine learning model accurately estimated scores from a depression questionnaire from complete and partial clinical notes, per a poster at the American Society of Clinical Psychopharmacology annual meeting.“In the real world, there’s a lot of missing data and [Patient Health Questionnaire-9] scores are commonly used and patients record them, but not](/_next/image/?url=https%3A%2F%2Fimages.ctfassets.net%2Fddhe5ahaolzf%2F2wrdaT8JqEIhQnO9DOVyde%2Fc04bff599118eda62ea91d22920aeb7e%2Fdoctor-at-computer_2020.jpg&w=3840&q=75)
