22 citations · 39 across the 7 of their papers we have counts for
7 papers
Agent Skill Evaluation and Evolution: Frameworks and Benchmarks
Kexin Ding, Yang Zhou, Can Jin +3
The growth of agent skills has transformed how agentic systems are built, evaluated, and deployed. As skill libraries continue to scale, rigorous evaluation becomes critical to ens…
Aligning Large Language Models with Healthcare Stakeholders: A Pathway to Trustworthy AI Integration
Kexin Ding, Mu Zhou, Akshay Chaudhari +2
The wide exploration of large language models (LLMs) raises the awareness of alignment between healthcare stakeholder preferences and model outputs. This alignment becomes a crucia…
MedForge: Building Medical Foundation Models Like Open Source Software Development
Zheling Tan, Kexin Ding, Jin Gao +4
Foundational models (FMs) have made significant strides in the healthcare domain. Yet the data silo challenge and privacy concern remain in healthcare systems, hindering safe medic…
Data-Centric Foundation Models in Computational Healthcare: A Survey
Yunkun Zhang, Jin Gao, Zheling Tan +5
The advent of foundation models (FMs) as an emerging suite of AI techniques has struck a wave of opportunities in computational healthcare. The interactive nature of these models,…
Statistical Inference on Grayscale Images via the Euler-Radon Transform
Kun Meng, Mattie Ji, Jinyu Wang +4
Tools from topological data analysis have been widely used to represent binary images in many scientific applications. Methods that aim to represent grayscale images (i.e., where p…
Pathology-and-genomics Multimodal Transformer for Survival Outcome Prediction
Kexin Ding, Mu Zhou, Dimitris N. Metaxas +1
Survival outcome assessment is challenging and inherently associated with multiple clinical factors (e.g., imaging and genomics biomarkers) in cancer. Enabling multimodal analytics…
Graph Convolutional Networks for Multi-modality Medical Imaging: Methods, Architectures, and Clinical Applications
Kexin Ding, Mu Zhou, Zichen Wang +4
Image-based characterization and disease understanding involve integrative analysis of morphological, spatial, and topological information across biological scales. The development…