Article

ConfidentNeuro: Conformal Prediction-Based Uncertainty Quantification for Hallucination Risk Scoring in LLM-Assisted Alzheimer's Clinical Decision Support

2026-05-29

Abstract excerpt

<title>Abstract</title> <p>Alzheimer's disease (AD) affects more than 55 million people worldwide. In recent years, clinical decision support (CDS) systems built on large language models (LLMs) have become increasingly common in neurological care. These models hallucinate, generating clinically plausible but factually incorrect responses. The existing evaluation methods measure overall accuracy, leaving clinician...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: 7733a052-3883-5be9-be25-be5b7cf4adfe
DOI: 10.21203/rs.3.rs-9707462/v1

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

ConfidentNeuro: Conformal Prediction-Based Uncertainty Quantification for Hallucination Risk Scoring in LLM-Assisted Alzheimer's Clinical Decision SupportDOI 10.21203/rs.3.rs-9707462/v1Read

Learning the Phenotype of Medical HallucinationsSemantic proximity Read

Rethinking Medical LLM Hallucinations: A System-Level SurveySemantic proximity Read

Large Language Models Are Highly Vulnerable to Adversarial Hallucination Attacks in Clinical Decision Support: A Multi-Model Assurance AnalysisSemantic proximity Read

Generative Large Language Models in the Clinical Management of Alzheimer’s Disease and Mild Cognitive ImpairmentSemantic proximity Read

An interdisciplinary, randomized, single-blind evaluation of state-of-the-art large language models for their implications and risks in medical diagnosis and managementSemantic proximity Read

Medical Hallucination in Foundation Models and Their Impact on HealthcareSemantic proximity Read

An auditable, retrieval-grounded agent architecture improves medical accuracy and conversational safety in language modelsSemantic proximity Read

A dataset for evaluating clinical research claims in large language modelsSemantic proximity Read

Domain-adapted language model using reinforcement learning for various dementiasSemantic proximity Read

Large Language Models in Alzheimer’s Care: Clinical Use Cases, Safety Challenges, and Implementation PathwaysSemantic proximity Read

RiskAgent: Autonomous Medical AI Copilot for Generalist Risk PredictionSemantic proximity Read

Multidimensional Evaluation of Large Language Models on the AAP In-Service Examination: Assessing Accuracy, Calibration, and Citation ReliabilitySemantic proximity Read