most citedPrompt Engineering for Healthcare: Methodologies and Applications

118 citations · 274 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2023★ 78 cited

CLIP in Medical Imaging: A Survey

Zihao Zhao, Yuxiao Liu, Han Wu +8

Contrastive Language-Image Pre-training (CLIP), a simple yet effective pre-training paradigm, successfully introduces text supervision to vision models. It has shown promising resu…

cs.CL2023★ 19 cited

Evaluating Large Language Models for Radiology Natural Language Processing

Zhengliang Liu, Tianyang Zhong, Yiwei Li +43

The rise of large language models (LLMs) has marked a pivotal shift in the field of natural language processing (NLP). LLMs have revolutionized a multitude of domains, and they hav…

cs.AI2023★ 44 cited

Artificial General Intelligence for Medical Imaging Analysis

Xiang Li, Lin Zhao, Lu Zhang +16

Large-scale Artificial General Intelligence (AGI) models, including Large Language Models (LLMs) such as ChatGPT/GPT-4, have achieved unprecedented success in a variety of general…

cs.AI2023★ 118 cited

Prompt Engineering for Healthcare: Methodologies and Applications

Jiaqi Wang, Enze Shi, Sigang Yu +21

Prompt engineering is a critical technique in the field of natural language processing that involves designing and optimizing the prompts used to input information into models, aim…

cs.CV2017★ 15 cited

Deep Embedding Convolutional Neural Network for Synthesizing CT Image from T1-Weighted MR Image

Lei Xiang, Qian Wang, Xiyao Jin +3

Recently, more and more attention is drawn to the field of medical image synthesis across modalities. Among them, the synthesis of computed tomography (CT) image from T1-weighted m…