Michael L. Birnbaum

schoolNorthwell Healthbar_chart#1972 Global Rank

Total Papers

HCI Rank

#1972

Research Areas

Years Active

Recent Publications

Missed Opportunities for Human-Centered AI Research: Understanding Stakeholder Collaboration in Mental Health AI Research

In the mental health domain, where AI technologies will impact their treatment and daily lives, patient engagement can be a key to designing human-centered technologies. CSCW and HCI researchers have delved into various facets of collaboration in AI research; however, previous research neglects the individuals who pro…

CHI '244th AuthorAI-Assisted Decision-Making & Automation +2

Patient Perspectives on AI-Driven Predictions of Schizophrenia Relapses: Understanding Concerns and Opportunities for Self-Care and Treatment

Early detection and intervention for relapse is important in the treatment of schizophrenia spectrum disorders. Researchers have developed AI models to predict relapse from patient-contributed data like social media. However, these models face challenges, including misalignment with practice and ethical issues related…

CSCW '235th+ AuthorMental Health II

Discussing Social Media During Psychotherapy Consultations: Patient Narratives and Privacy Implications

Social media platforms are being utilized by individuals with mental illness for engaging in self-disclosure, finding support, or navigating treatment journeys. Individuals also increasingly bring their social media data to psychotherapy consultations. This emerging practice during psychotherapy can help us to better…

CSCW '215th+ AuthorPersonal and Mental Health

A Social Media Study on Mental Health Status Transitions Surrounding Psychiatric Hospitalizations

For people diagnosed with a mental illness, psychiatric hospitalization is one step in a long journey, consisting of clinical recovery such as removal of symptoms, and social reintegration involving resuming social roles and responsibilities, overcoming stigma and self-maintenance of the condition. Both clinical recov…

CHI '192nd AuthorExplainable AI (XAI) +1

Methodological Gaps in Predicting Mental Health States from Social Media: Triangulating Diagnostic Signals

A growing body of research is combining social media data with machine learning to predict mental health states of individuals. An implication of this research lies in informing evidence-based diagnosis and treatment. However, obtaining clinically valid diagnostic information from sensitive patient populations is chal…

CSCW '183rd AuthorLanguage and Linguistics

Linguistic Markers Indicating Therapeutic Outcomes of Social Media Disclosures of Schizophrenia

Self-disclosure of stigmatized conditions is known to yield therapeutic benefits. Social media sites are emerging as promising platforms enabling disclosure around a variety of stigmatized concerns, including mental illness. What kind of behavioral changes precede and follow such disclosures? Do the therapeutic benefi…

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