Research map / Large language models / AI and society
Knowledge-Infused Learning for Developing a Mental Health Diagnostic Copilot in Healthcare Systems
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Proposes a knowledge-infused, multi-turn AI diagnostic copilot for mental health that works alongside clinicians, with a planned (not yet implemented) evaluation design.
Problem
Mental health diagnosis and treatment disparities for underserved communities such as African Americans, where static AI diagnostic systems lack real-time multi-turn patient interaction and clinical grounding.
Approach
Combine Knowledge-Infused Learning (clinical ontologies SNOMED CT and UMLS embedded into decision trees and ensembles via modified splitting criteria) with multi-turn conversational feedback and clinician instructability via DPO or KTO.
Key results
- No empirical results are reported; the paper proposes a research plan and planned evaluation metrics only.
Limitations
- No implementation or experimental results are presented.
- Evaluation plan is described only at a high level without baselines or quantitative targets.
- Dataset use for mental health conversations and EHRs is not detailed for privacy or validity.
Experimental setup
Datasets: ESCON IHMI SMHD Primate SNOMED CT UMLS
Metrics: clinical entity overlap score NLI-based logical coherence cosine similarity BERTScore
Builds on: Knowledge-Infused Learning Direct Preference Optimization Kahneman-Tversky Optimization
Closest papers by meaning
- KGARevion: An AI Agent for Knowledge-Intensive Biomedical QA (ICLR 2025 · similarity 0.81)
- CARE: Towards Clinical Accountability in Multi-Modal Medical Reasoning with an Evidence-Grounded Agentic Framework (ICLR 2026 · similarity 0.81)
- Doctor-R1: Mastering Clinical Inquiry with Experiential Agentic Reinforcement Learning (ICLR 2026 · similarity 0.81)
- Position: Beyond Assistance – Reimagining LLMs as Ethical and Adaptive Co-Creators in Mental Health Care (ICML 2025 · similarity 0.80)
- Visual and Domain Knowledge for Professional-level Graph-of-Thought Medical Reasoning (ICML 2025 · similarity 0.80)
- ED-Copilot: Reduce Emergency Department Wait Time with Language Model Diagnostic Assistance (ICML 2024 · similarity 0.80)
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