2.2k citations · 6.2k across the 59 of their papers we have counts for
17 papers · 1 filter
When an Image is Worth 1,024 x 1,024 Words: A Case Study in Computational Pathology
Wenhui Wang, Shuming Ma, Hanwen Xu +4
This technical report presents LongViT, a vision Transformer that can process gigapixel images in an end-to-end manner. Specifically, we split the gigapixel image into a sequence o…
Cautionary Tales on Synthetic Controls in Survival Analyses
Alicia Curth, Hoifung Poon, Aditya V. Nori +1
Synthetic control (SC) methods have gained rapid popularity in economics recently, where they have been applied in the context of inferring the effects of treatments on standard co…
Can Generalist Foundation Models Outcompete Special-Purpose Tuning? Case Study in Medicine
Harsha Nori, Yin Tat Lee, Sheng Zhang +15
Generalist foundation models such as GPT-4 have displayed surprising capabilities in a wide variety of domains and tasks. Yet, there is a prevalent assumption that they cannot matc…
DocLens: Multi-aspect Fine-grained Evaluation for Medical Text Generation
Yiqing Xie, Sheng Zhang, Hao Cheng +6
Medical text generation aims to assist with administrative work and highlight salient information to support decision-making. To reflect the specific requirements of medical text,…
TRIALSCOPE: A Unifying Causal Framework for Scaling Real-World Evidence Generation with Biomedical Language Models
Javier González, Risa Ueno, Cliff Wong +12
The rapid digitization of real-world data presents an unprecedented opportunity to optimize healthcare delivery and accelerate biomedical discovery. However, these data are often f…
Exploring the Boundaries of GPT-4 in Radiology
Qianchu Liu, Stephanie Hyland, Shruthi Bannur +16
The recent success of general-domain large language models (LLMs) has significantly changed the natural language processing paradigm towards a unified foundation model across domai…
BiomedJourney: Counterfactual Biomedical Image Generation by Instruction-Learning from Multimodal Patient Journeys
Yu Gu, Jianwei Yang, Naoto Usuyama +5
Rapid progress has been made in instruction-learning for image editing with natural-language instruction, as exemplified by InstructPix2Pix. In biomedicine, such methods can be app…
Scaling Clinical Trial Matching Using Large Language Models: A Case Study in Oncology
Cliff Wong, Sheng Zhang, Yu Gu +8
Clinical trial matching is a key process in health delivery and discovery. In practice, it is plagued by overwhelming unstructured data and unscalable manual processing. In this pa…
UniversalNER: Targeted Distillation from Large Language Models for Open Named Entity Recognition
Wenxuan Zhou, Sheng Zhang, Yu Gu +2
Large language models (LLMs) have demonstrated remarkable generalizability, such as understanding arbitrary entities and relations. Instruction tuning has proven effective for dist…
Distilling Large Language Models for Biomedical Knowledge Extraction: A Case Study on Adverse Drug Events
Yu Gu, Sheng Zhang, Naoto Usuyama +8
Large language models (LLMs), such as GPT-4, have demonstrated remarkable capabilities across a wide range of tasks, including health applications. In this paper, we study how LLMs…
Pareto Optimal Learning for Estimating Large Language Model Errors
Theodore Zhao, Mu Wei, J. Samuel Preston +1
Large Language Models (LLMs) have shown impressive abilities in many applications. When a concrete and precise answer is desired, it is important to have a quantitative estimation…
LLaVA-Med: Training a Large Language-and-Vision Assistant for Biomedicine in One Day
Chunyuan Li, Cliff Wong, Sheng Zhang +6
Conversational generative AI has demonstrated remarkable promise for empowering biomedical practitioners, but current investigations focus on unimodal text. Multimodal conversation…
Self-Verification Improves Few-Shot Clinical Information Extraction
Zelalem Gero, Chandan Singh, Hao Cheng +4
Extracting patient information from unstructured text is a critical task in health decision-support and clinical research. Large language models (LLMs) have shown the potential to…
Compositional Zero-Shot Domain Transfer with Text-to-Text Models
Fangyu Liu, Qianchu Liu, Shruthi Bannur +9
Label scarcity is a bottleneck for improving task performance in specialised domains. We propose a novel compositional transfer learning framework (DoT5 - domain compositional zero…
Context-faithful Prompting for Large Language Models
Wenxuan Zhou, Sheng Zhang, Hoifung Poon +1
Large language models (LLMs) encode parametric knowledge about world facts and have shown remarkable performance in knowledge-driven NLP tasks. However, their reliance on parametri…
BiomedCLIP: a multimodal biomedical foundation model pretrained from fifteen million scientific image-text pairs
Sheng Zhang, Yanbo Xu, Naoto Usuyama +21
Biomedical data is inherently multimodal, comprising physical measurements and natural language narratives. A generalist biomedical AI model needs to simultaneously process differe…
BLIAM: Literature-based Data Synthesis for Synergistic Drug Combination Prediction
Cai Yang, Addie Woicik, Hoifung Poon +1
Language models pre-trained on scientific literature corpora have substantially advanced scientific discovery by offering high-quality feature representations for downstream applic…