output
20202025
most citedAutomatic Personalized Impression Generation for PET Reports Using Large Language Models

30 citations

5 papers

cs.LG2025★ 1 cited

Assay2Mol: large language model-based drug design using BioAssay context

Yifan Deng, Spencer S. Ericksen, Anthony Gitter

Scientific databases aggregate vast amounts of quantitative data alongside descriptive text. In biochemistry, molecule screening assays evaluate candidate molecules' functional res…

cs.LG2024★ 6 cited

Chemical Language Model Linker: blending text and molecules with modular adapters

Yifan Deng, Spencer S. Ericksen, Anthony Gitter

The development of large language models and multi-modal models has enabled the appealing idea of generating novel molecules from text descriptions. Generative modeling would shift…

cs.CV2024★ 1 cited

Automatic Quantification of Serial PET/CT Images for Pediatric Hodgkin Lymphoma Patients Using a Longitudinally-Aware Segmentation Network

Xin Tie, Muheon Shin, Changhee Lee +10

: Automatic quantification of longitudinal changes in PET scans for lymphoma patients has proven challenging, as residual disease in interim-therapy scans is ofte…

cs.AI2023★ 30 cited

Automatic Personalized Impression Generation for PET Reports Using Large Language Models

Xin Tie, Muheon Shin, Ali Pirasteh +8

In this study, we aimed to determine if fine-tuned large language models (LLMs) can generate accurate, personalized impressions for whole-body PET reports. Twelve language models w…

stat.ME2020★ 11 cited

MixTwice: large-scale hypothesis testing for peptide arrays by variance mixing

Zihao Zheng, Aisha M. Mergaert, Irene M. Ong +2

Peptide microarrays have emerged as a powerful technology in immunoproteomics as they provide a tool to measure the abundance of different antibodies in patient serum samples. The…