A comprehensive survey on evaluating large language model applications in the medical industry
Y Huang, K Tang, M Chen, B Wang - arxiv preprint arxiv:2404.15777, 2024 - arxiv.org
Since the inception of the Transformer architecture in 2017, Large Language Models (LLMs)
such as GPT and BERT have evolved significantly, impacting various industries with their …
such as GPT and BERT have evolved significantly, impacting various industries with their …
BioBART: Pretraining and evaluation of a biomedical generative language model
Pretrained language models have served as important backbones for natural language
processing. Recently, in-domain pretraining has been shown to benefit various domain …
processing. Recently, in-domain pretraining has been shown to benefit various domain …
[HTML][HTML] A comprehensive evaluation of large language models on benchmark biomedical text processing tasks
Abstract Recently, Large Language Models (LLMs) have demonstrated impressive
capability to solve a wide range of tasks. However, despite their success across various …
capability to solve a wide range of tasks. However, despite their success across various …
Paper Plain: Making Medical Research Papers Approachable to Healthcare Consumers with Natural Language Processing
When seeking information not covered in patient-friendly documents, healthcare consumers
may turn to the research literature. Reading medical papers, however, can be a challenging …
may turn to the research literature. Reading medical papers, however, can be a challenging …
[HTML][HTML] Exploring the efficacy of large language models in summarizing mental health counseling sessions: benchmark study
Background Comprehensive session summaries enable effective continuity in mental health
counseling, facilitating informed therapy planning. However, manual summarization …
counseling, facilitating informed therapy planning. However, manual summarization …
Evaluation of chatgpt on biomedical tasks: A zero-shot comparison with fine-tuned generative transformers
ChatGPT is a large language model developed by OpenAI. Despite its impressive
performance across various tasks, no prior work has investigated its capability in the …
performance across various tasks, no prior work has investigated its capability in the …
Data augmentation for improving emotion recognition in software engineering communication
Emotions (eg, Joy, Anger) are prevalent in daily software engineering (SE) activities, and are
known to be significant indicators of work productivity (eg, bug fixing efficiency). Recent …
known to be significant indicators of work productivity (eg, bug fixing efficiency). Recent …
An Overview of Deep Neural Networks for Few-Shot Learning
J Zhao, L Kong, J Lv - Big Data Mining and Analytics, 2024 - ieeexplore.ieee.org
Recent advancements in deep learning have led to significant breakthroughs across various
fields. However, these methods often require extensive labeled data for optimal …
fields. However, these methods often require extensive labeled data for optimal …
A survey on medical document summarization
The internet has had a dramatic effect on the healthcare industry, allowing documents to be
saved, shared, and managed digitally. This has made it easier to locate and share important …
saved, shared, and managed digitally. This has made it easier to locate and share important …
Detection, disambiguation, re-ranking: Autoregressive entity linking as a multi-task problem
We propose an autoregressive entity linking model, that is trained with two auxiliary tasks,
and learns to re-rank generated samples at inference time. Our proposed novelties address …
and learns to re-rank generated samples at inference time. Our proposed novelties address …