Multimodal Prediction of Obsessive-Compulsive Disorder and Comorbid Depression Severity and Energy Delivered by Deep Brain Electrodes.

To develop reliable, valid, and efficient measures of obsessive-compulsive disorder (OCD) severity, comorbid depression severity, and total electrical energy delivered (TEED) by deep brain stimulation (DBS), we trained and compared random forests regression models in a clinical trial of participants receiving DBS for refractory OCD. Six participants were recorded during open-ended interviews at pre- and post-surgery baselines and then at 3-month intervals following DBS activation. Ground-truth severity was assessed by clinical interview and self-report.

SMURF: Statistical Modality Uniqueness and Redundancy Factorization.

Multimodal late fusion is a well-performing fusion method that sums the outputs of separately processed modalities, so-called modality contributions, to create a prediction; for example, summing contributions from vision, acoustic, and language to predict affective states. In this paper, our primary goal is to improve the interpretability of what modalities contribute to the prediction in late fusion models. More specifically, we want to factorize modality contributions into what is consistently shared by at least two modalities (pairwise redundant contributions) and what the remaining modality-specific contributions are (unique contributions).

Learning to Generate Context-Sensitive Backchannel Smiles for Embodied AI Agents with Applications in Mental Health Dialogues.

Addressing the critical shortage of mental health resources for effective screening, diagnosis, and treatment remains a significant challenge. This scarcity underscores the need for innovative solutions, particularly in enhancing the accessibility and efficacy of therapeutic support. Embodied agents with advanced interactive capabilities emerge as a promising and cost-effective supplement to traditional caregiving methods.

Physician preferences of biomarker testing strategies in newly diagnosed stage IV non-small cell lung cancer patients.

To understand physicians' attitudes and behaviors regarding EGFR testing and retesting strategies in newly diagnosed metastatic non-small cell lung cancer patients. Oncologists and pathologists completed an online, cross-sectional survey. Most oncologists (73.

Aperiodic (1/f) neural activity robustly tracks symptom severity changes in treatment-resistant depression.

Background: A reliable physiological biomarker for Major Depressive Disorder is essential for developing and optimizing neuromodulatory treatment paradigms. This study investigates a passive electrophysiologic biomarker that tracks changes in depressive symptom severity on the order of minutes to hours.

Methods: We analyze brief recordings from intracranial electrodes implanted deep in the brain during a clinical trial of deep brain stimulation for treatment-resistant depression in 5 human subjects (n= 3, n = 2).