6 papers
Developing Fairness-Aware Task Decomposition to Improve Equity in Post-Spinal Fusion Complication Prediction
Yining Yuan, J. Ben Tamo, Wenqi Shi +5
Fairness in clinical prediction models remains a persistent challenge, particularly in high-stakes applications such as spinal fusion surgery for scoliosis, where patient outcomes…
Leveraging Evidence-Guided LLMs to Enhance Trustworthy Depression Diagnosis
Yining Yuan, J. Ben Tamo, Micky C. Nnamdi +2
Large language models (LLMs) show promise in automating clinical diagnosis, yet their non-transparent decision-making and limited alignment with diagnostic standards hinder trust a…
MetaBench: A Multi-task Benchmark for Assessing LLMs in Metabolomics
Yuxing Lu, Xukai Zhao, J. Ben Tamo +6
Large Language Models (LLMs) have demonstrated remarkable capabilities on general text; however, their proficiency in specialized scientific domains that require deep, interconnect…
Causal Machine Learning for Surgical Interventions
J. Ben Tamo, Nishant S. Chouhan, Micky C. Nnamdi +6
Surgical decision-making is complex and requires understanding causal relationships between patient characteristics, interventions, and outcomes. In high-stakes settings like spina…
MENDR: Manifold Explainable Neural Data Representations
Matthew Chen, Micky Nnamdi, Justin Shao +7
Foundation models for electroencephalography (EEG) signals have recently demonstrated success in learning generalized representations of EEGs, outperforming specialized models in v…
Novel Extraction of Discriminative Fine-Grained Feature to Improve Retinal Vessel Segmentation
Shuang Zeng, Chee Hong Lee, Micky C Nnamdi +9
Retinal vessel segmentation is a vital early detection method for several severe ocular diseases. Despite significant progress in retinal vessel segmentation with the advancement o…