With the most robust behavioral health database of its kind and seamless AI-powered analytic tools, NeuroBlu enables uniquely powerful evidence generation. Explore the use cases below to discover how you can address key research questions to drive clinical and commercial success in behavioral health. To learn more, please contact us at info@neuroblu.ai.

Clinical Development

Leveraging NeuroBlu NLP to enhance understanding of the patient journey — an approach to analyzing psychotic disorders

Holmusk has now developed a NeuroBlu NLP psychotic disorders model, which identifies a selected set of positive symptoms associated with psychotic disorders, and negative symptoms associated with a subset of these disorders.
February 15, 2024
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Data overview

Fact Sheet: NeuroBlu V3.7

The Fact Sheet provides a deep dive into characteristics of our latest data expansion (V3.7), including geographic representativeness, site diversity, and outcome measure density.
January 17, 2024
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Clinical Development

Leveraging NeuroBlu to build, visualize, and analyze real-world cohorts for behavioral health

Use the Cohort Explorer feature in NeuroBlu to compare patients diagnosed with major depressive disorder with and without substance use disorders.
August 28, 2023
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Clinical Development

NeuroBlu NLP extracts key insights from unstructured data to enhance behavioral health research

Leverage NeuroBlu NLP to generate analyzable data on symptomatology, such as the presence of anhedonia in patients with depressive disorders, and increase cohort sizes by up to 25%.
August 30, 2023
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Clinical Development

Gaining better understanding of healthcare utilization through building patient journeys

Obtain a comprehensive view of how patients move through the health care systems, track patterns, and identify changes in conditions.
May 31, 2023
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Clinical Development

Conducting comparative effectiveness studies using standardized measures

Gain insight into how different drugs impact patient outcomes in order to support decision-making during the drug development lifecycle.
May 24, 2023
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Clinical Development

Using NLP-derived negative symptoms to compare treatment effectiveness for schizophrenia

Leverage granular, NLP-enriched data on negative symptoms to understand treatment effectiveness in schizophrenia and support development of treatments to target negative symptoms.
May 17, 2023
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