2 citations · 10 across the 12 of their papers we have counts for
12 papers
iSight: Towards expert-AI co-assessment for improved immunohistochemistry staining interpretation
Jacob S. Leiby, Jialu Yao, Pan Lu +17
Immunohistochemistry (IHC) provides information on protein expression in tissue sections and is commonly used to support pathology diagnosis and disease triage. While AI models for…
STEER: Inference-Time Risk Control via Constrained Quality-Diversity Search
Eric Yang, Jong Ha Lee, Jonathan Amar +2
Large Language Models (LLMs) trained for average correctness often exhibit mode collapse, producing narrow decision behaviors on tasks where multiple responses may be reasonable. T…
DynaWeb: Model-Based Reinforcement Learning of Web Agents
Hang Ding, Peidong Liu, Junqiao Wang +7
The development of autonomous web agents, powered by Large Language Models (LLMs) and reinforcement learning (RL), represents a significant step towards general-purpose AI assistan…
An AI-Based Behavioral Health Safety Filter and Dataset for Identifying Mental Health Crises in Text-Based Conversations
Benjamin W. Nelson, Celeste Wong, Matthew T. Silvestrini +6
Large language models often mishandle psychiatric emergencies, offering harmful or inappropriate advice and enabling destructive behaviors. This study evaluated the Verily behavior…
FHIR-AgentBench: Benchmarking LLM Agents for Realistic Interoperable EHR Question Answering
Gyubok Lee, Elea Bach, Eric Yang +5
The recent shift toward the Health Level Seven Fast Healthcare Interoperability Resources (HL7 FHIR) standard opens a new frontier for clinical AI, demanding LLM agents to navigate…
AI Agents for Conversational Patient Triage: Preliminary Simulation-Based Evaluation with Real-World EHR Data
Sina Rashidian, Nan Li, Jonathan Amar +7
Background: We present a Patient Simulator that leverages real world patient encounters which cover a broad range of conditions and symptoms to provide synthetic test subjects for…
Sleepless Nights, Sugary Days: Creating Synthetic Users with Health Conditions for Realistic Coaching Agent Interactions
Taedong Yun, Eric Yang, Mustafa Safdari +13
We present an end-to-end framework for generating synthetic users for evaluating interactive agents designed to encourage positive behavior changes, such as in health and lifestyle…
MPLite: Multi-Aspect Pretraining for Mining Clinical Health Records
Eric Yang, Pengfei Hu, Xiaoxue Han +1
The adoption of digital systems in healthcare has resulted in the accumulation of vast electronic health records (EHRs), offering valuable data for machine learning methods to pred…
From Barriers to Tactics: A Behavioral Science-Informed Agentic Workflow for Personalized Nutrition Coaching
Eric Yang, Tomas Garcia, Hannah Williams +7
Effective management of cardiometabolic conditions requires sustained positive nutrition habits, often hindered by complex and individualized barriers. Direct human management is s…
Context-Aware SQL Error Correction Using Few-Shot Learning -- A Novel Approach Based on NLQ, Error, and SQL Similarity
Divyansh Jain, Eric Yang
In recent years, the demand for automated SQL generation has increased significantly, driven by the need for efficient data querying in various applications. However, generating ac…
The Geometry of Queries: Query-Based Innovations in Retrieval-Augmented Generation for Healthcare QA
Eric Yang, Jonathan Amar, Jong Ha Lee +2
Deploying Large Language Models (LLMs) for healthcare question answering requires robust methods to ensure accuracy and reliability. This work introduces Query-Based Retrieval Augm…
Selective Fine-tuning on LLM-labeled Data May Reduce Reliance on Human Annotation: A Case Study Using Schedule-of-Event Table Detection
Bhawesh Kumar, Jonathan Amar, Eric Yang +2
Large Language Models (LLMs) have demonstrated their efficacy across a broad spectrum of tasks in healthcare applications. However, often LLMs need to be fine-tuned on task-specifi…