{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T01:41:03Z","timestamp":1760060463016,"version":"build-2065373602"},"reference-count":71,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2025,8,23]],"date-time":"2025-08-23T00:00:00Z","timestamp":1755907200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Biomimetics"],"abstract":"<jats:p>Anxiety and depression affect millions worldwide, yet stigma and long wait times often delay access to care. Mobile mental health apps can decrease these barriers by offering on-demand screening and support. Nevertheless, many machine and deep learning methods used in such tools perform poorly under severe class imbalance, yielding biased, poorly calibrated predictions. To address this challenge, this study proposes MCoG-LDPSNet, a brain-inspired model that combines dual, orthogonal encoding pathways with a novel Loss-Driven Parametric Swish (LDPS) activation. LDPS implements a neurobiologically motivated adaptive-gain mechanism via a learnable \u03b2 parameter driven by calibration and confidence-aware loss signals that amplifies minority-class patterns while preserving overall reliability, enabling robust predictions under severe data imbalance. On a benchmark mental health corpus, MCoG-LDPSNet achieved AUROC = 0.9920 and G-mean = 0.9451, outperforming traditional baselines like GLMs, XGBoost, state-of-the-art deep models (CNN-BiLSTM-ATTN), and transformer-based approaches. After transfer learning to social media text, the MCoG-LDPSNet maintained a near-perfect AUROC of 0.9937. Integrated into the EmotiZen App with enhanced app features, MCoG-LDPSNet was associated with substantial symptom reductions (anxiety 28.2%; depression 42.1%). These findings indicate that MCoG-LDPSNet is an accurate, imbalance-aware solution suitable for scalable mobile screening of individuals for anxiety and depression.<\/jats:p>","DOI":"10.3390\/biomimetics10090563","type":"journal-article","created":{"date-parts":[[2025,8,25]],"date-time":"2025-08-25T00:09:53Z","timestamp":1756080593000},"page":"563","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Mobile Mental Health Screening in EmotiZen via the Novel Brain-Inspired MCoG-LDPSNet"],"prefix":"10.3390","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0009-0004-1261-0073","authenticated-orcid":false,"given":"Christos","family":"Bormpotsis","sequence":"first","affiliation":[{"name":"Department of Artificial Intelligence and Computational Neuroscience, EmotiZen GmbH, 55122 Mainz, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8934-670X","authenticated-orcid":false,"given":"Maria","family":"Anagnostouli","sequence":"additional","affiliation":[{"name":"Research Immunogenetics Laboratory, First Department of Neurology, School of Medicine, National and Kapodistrian University of Athens, Aeginition University Hospital, Vas. Sofias 72-74, 11528 Athens, Greece"},{"name":"Multiple Sclerosis and Demyelinating Diseases Unit, Center of Expertise for Rare Demyelinating and Autoimmune Diseases of CNS, First Department of Neurology, School of Medicine, National and Kapodistrian University of Athens, Aeginition University Hospital, 11528 Athens, Greece"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mohamed","family":"Sedky","sequence":"additional","affiliation":[{"name":"Department of Computing, School of Digital, Technology, Innovation and Business (DTIB), The University of Staffordshire, College Road, Stoke-on-Trent ST4 2DE, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7499-4034","authenticated-orcid":false,"given":"Eleni","family":"Jelastopulu","sequence":"additional","affiliation":[{"name":"Department of Public Health, School of Medicine, University of Patras, 26504 Patras, Greece"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1636-5955","authenticated-orcid":false,"given":"Asma","family":"Patel","sequence":"additional","affiliation":[{"name":"Department of Artificial Intelligence and Computational Neuroscience, EmotiZen GmbH, 55122 Mainz, Germany"},{"name":"Department of The Operations and Information Management, Aston Business School, Aston University, Birmingham B4 7ET, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2025,8,23]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Fan, Y., Fan, A., Yang, Z., and Fan, D. 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