- An artificial intelligence framework for end-to-end rare disease phenotyping from clinical notes using large language models
Cathy Shyr, Yan Hu, Rory J. Tinker, Thomas A. Cassini, Kevin W. Byram · Feb 23, 2026 · Citations: 0
Expert Verification Automatic Metrics
Existing artificial intelligence approaches typically optimize individual components of phenotyping but do not operationalize the full clinical workflow of extracting features from clinical text, standardizing them to Human Phenotype…
- TherapyProbe: Generating Design Knowledge for Relational Safety in Mental Health Chatbots Through Adversarial Simulation
Joydeep Chandra, Satyam Kumar Navneet, Yong Zhang · Feb 26, 2026 · Citations: 0
Expert Verification Simulation Env Multi Agent
As mental health chatbots proliferate to address the global treatment gap, a critical question emerges: How do we design for relational safety the quality of interaction patterns that unfold across conversations rather than the correctness…
- Modeling Expert AI Diagnostic Alignment via Immutable Inference Snapshots
Dimitrios P. Panagoulias, Evangelia-Aikaterini Tsichrintzi, Georgios Savvidis, Evridiki Tsoureli-Nikita · Feb 26, 2026 · Citations: 0
Expert Verification Automatic Metrics
Human-in-the-loop validation is essential in safety-critical clinical AI, yet the transition between initial model inference and expert correction is rarely analyzed as a structured signal.
- Decomposing Physician Disagreement in HealthBench
Satya Borgohain, Roy Mariathas · Feb 26, 2026 · Citations: 0
Rubric Rating
We decompose physician disagreement in the HealthBench medical AI evaluation dataset to understand where variance resides and what observable features can explain it.
- Think$^{2}$: Grounded Metacognitive Reasoning in Large Language Models
Abraham Paul Elenjical, Vivek Hruday Kavuri, Vasudeva Varma · Feb 21, 2026 · Citations: 0
Pairwise Preference Human Eval
We introduce a psychologically grounded metacognitive framework that operationalizes Ann Brown's regulatory cycle (Planning, Monitoring, and Evaluation) as a structured prompting architecture, and study its integration within a lightweight…
- Multi-Objective Alignment of Language Models for Personalized Psychotherapy
Mehrab Beikzadeh, Yasaman Asadollah Salmanpour, Ashima Suvarna, Sriram Sankararaman, Matteo Malgaroli · Feb 17, 2026 · Citations: 0
Pairwise PreferenceExpert Verification Automatic Metrics
While AI systems show therapeutic promise, current alignment approaches optimize objectives independently, failing to balance patient preferences with clinical safety.
- MedXIAOHE: A Comprehensive Recipe for Building Medical MLLMs
Baorong Shi, Bo Cui, Boyuan Jiang, Deli Yu, Fang Qian · Feb 13, 2026 · Citations: 0
Pairwise PreferenceRubric Rating Long Horizon
MedXIAOHE achieves state-of-the-art performance across diverse medical benchmarks and surpasses leading closed-source multimodal systems on multiple capabilities.
- Assessing Risks of Large Language Models in Mental Health Support: A Framework for Automated Clinical AI Red Teaming
Ian Steenstra, Paola Pedrelli, Weiyan Shi, Stacy Marsella, Timothy W. Bickmore · Feb 23, 2026 · Citations: 0
Red Team Simulation Env
Large Language Models (LLMs) are increasingly utilized for mental health support; however, current safety benchmarks often fail to detect the complex, longitudinal risks inherent in therapeutic dialogue.
- CUICurate: A GraphRAG-based Framework for Automated Clinical Concept Curation for NLP applications
Victoria Blake, Mathew Miller, Jamie Novak, Sze-yuan Ooi, Blanca Gallego · Feb 20, 2026 · Citations: 0
Expert Verification Automatic Metrics
The framework was evaluated on five lexically heterogeneous clinical concepts against a manually curated benchmark and gold-standard concept sets.
- MEDSYN: Benchmarking Multi-EviDence SYNthesis in Complex Clinical Cases for Multimodal Large Language Models
Boqi Chen, Xudong Liu, Jiachuan Peng, Marianne Frey-Marti, Bang Zheng · Feb 25, 2026 · Citations: 0
Expert Verification Automatic Metrics
Multimodal large language models (MLLMs) have shown great potential in medical applications, yet existing benchmarks inadequately capture real-world clinical complexity.
- SurGo-R1: Benchmarking and Modeling Contextual Reasoning for Operative Zone in Surgical Video
Guanyi Qin, Xiaozhen Wang, Zhu Zhuo, Chang Han Low, Yuancan Xiao · Feb 25, 2026 · Citations: 0
Expert Verification Automatic Metrics
Existing AI systems offer binary safety verification or static detection, ignoring the phase-dependent nature of intraoperative reasoning.
- What Makes a Good Doctor Response? An Analysis on a Romanian Telemedicine Platform
Adrian Cosma, Cosmin Dumitrache, Emilian Radoi · Feb 19, 2026 · Citations: 0
Expert Verification Automatic Metrics
As platforms increasingly rely on patient ratings and feedback, clinicians face growing pressure to maintain satisfaction scores, even though these evaluations often reflect communication quality more than clinical accuracy.
- Diffusion Model in Latent Space for Medical Image Segmentation Task
Huynh Trinh Ngoc, Toan Nguyen Hai, Ba Luong Son, Long Tran Quoc · Dec 1, 2025 · Citations: 0
Expert Verification Automatic Metrics
Medical image segmentation is crucial for clinical diagnosis and treatment planning.
- OMGs: A multi-agent system supporting MDT decision-making across the ovarian tumour care continuum
Yangyang Zhang, Zilong Wang, Jianbo Xu, Yongqi Chen, Chu Han · Feb 14, 2026 · Citations: 0
Expert Verification Multi Agent
Here we present OMGs (Ovarian tumour Multidisciplinary intelligent aGent System), a multi-agent AI framework where domain-specific agents deliberate collaboratively to integrate multidisciplinary evidence and generate MDT-style…
- Continuous Telemonitoring of Heart Failure using Personalised Speech Dynamics
Yue Pan, Xingyao Wang, Hanyue Zhang, Liwei Liu, Changxin Li · Feb 23, 2026 · Citations: 0
Automatic Metrics Long Horizon
The model's high sensitivity was further corroborated by additional follow-up data, confirming its efficacy in predicting HF deterioration and its potential to secure patient safety in remote, home-based settings.
- pMoE: Prompting Diverse Experts Together Wins More in Visual Adaptation
Shentong Mo, Xufang Luo, Dongsheng Li · Feb 26, 2026 · Citations: 0
Expert Verification
In this work, we propose a novel Mixture-of-Experts prompt tuning method called pMoE, which leverages the strengths of multiple expert domains through expert-specialized prompt tokens and the learnable dispatcher, effectively combining…
- AgenticRAGTracer: A Hop-Aware Benchmark for Diagnosing Multi-Step Retrieval Reasoning in Agentic RAG
Qijie You, Wenkai Yu, Wentao Zhang · Feb 22, 2026 · Citations: 0
Automatic Metrics Long Horizon
With the rapid advancement of agent-based methods in recent years, Agentic RAG has undoubtedly become an important research direction.
- A Multi-Agent Framework for Medical AI: Leveraging Fine-Tuned GPT, LLaMA, and DeepSeek R1 for Evidence-Based and Bias-Aware Clinical Query Processing
Naeimeh Nourmohammadi, Md Meem Hossain, The Anh Han, Safina Showkat Ara, Zia Ush Shamszaman · Feb 15, 2026 · Citations: 0
Automatic Metrics Multi Agent
We propose a multi-agent medical QA framework that combines complementary LLMs with evidence retrieval, uncertainty estimation, and bias checks to improve answer reliability.
- Assessing Large Language Models for Medical QA: Zero-Shot and LLM-as-a-Judge Evaluation
Shefayat E Shams Adib, Ahmed Alfey Sani, Ekramul Alam Esham, Ajwad Abrar, Tareque Mohmud Chowdhury · Feb 16, 2026 · Citations: 0
Llm As JudgeAutomatic Metrics
We are using a zero-shot evaluation methodology and using BLEU and ROUGE metrics to evaluate performance without specialized fine-tuning.
- INSURE-Dial: A Phase-Aware Conversational Dataset & Benchmark for Compliance Verification and Phase Detection
Shubham Kulkarni, Alexander Lyzhov, Preetam Joshi, Shiva Chaitanya · Jan 28, 2026 · Citations: 0
Automatic Metrics Web Browsing
We introduce INSURE-Dial, to our knowledge the first public benchmark for developing and assessing compliance-aware voice agents for phase-aware call auditing with span-based compliance verification.
- Cold-Start Personalization via Training-Free Priors from Structured World Models
Avinandan Bose, Shuyue Stella Li, Faeze Brahman, Pang Wei Koh, Simon Shaolei Du · Feb 16, 2026 · Citations: 0
Pairwise Preference
Cold-start personalization requires inferring user preferences through interaction when no user-specific historical data is available.
- AgenticSum: An Agentic Inference-Time Framework for Faithful Clinical Text Summarization
Fahmida Liza Piya, Rahmatollah Beheshti · Feb 23, 2026 · Citations: 0
Human EvalLlm As Judge
We present AgenticSum, an inference-time, agentic framework that separates context selection, generation, verification, and targeted correction to reduce hallucinated content.
