Using Bottleneck Adapters to Identify Cancer in Clinical Notes under Low-Resource Constraints

17 October 2022

Papers citing "Using Bottleneck Adapters to Identify Cancer in Clinical Notes under Low-Resource Constraints"

7 / 7 papers shown

Title
Prompt engineering paradigms for medical applications: scoping review and recommendations for better practices Jamil Zaghir Marco Naguib Mina Bjelogrlic Aurélie Névéol Xavier Tannier Christian Lovis AI4CE LM&MA 35 6 0 02 May 2024
Foundation Model for Advancing Healthcare: Challenges, Opportunities, and Future Directions Yuting He Fuxiang Huang Xinrui Jiang Yuxiang Nie Minghao Wang Jiguang Wang Hao Chen LM&MA AI4CE 71 27 0 04 Apr 2024
Efficient Multi-domain Text Recognition Deep Neural Network Parameterization with Residual Adapters Jiayou Chao Wei Zhu 34 0 0 01 Jan 2024
Not Enough Labeled Data? Just Add Semantics: A Data-Efficient Method for Inferring Online Health Texts Joseph Gatto S. Preum AI4MH 35 1 0 18 Sep 2023
A Brief Review of Hypernetworks in Deep Learning Vinod Kumar Chauhan Jiandong Zhou Ping Lu Soheila Molaei David A. Clifton 27 94 0 12 Jun 2023
The Power of Scale for Parameter-Efficient Prompt Tuning Brian Lester Rami Al-Rfou Noah Constant VPVLM 280 3,848 0 18 Apr 2021
Clinical XLNet: Modeling Sequential Clinical Notes and Predicting Prolonged Mechanical Ventilation Kexin Huang Abhishek Singh Sitong Chen E. Moseley Chih-ying Deng Naomi George C. Lindvall 59 57 0 27 Dec 2019