Zobrazeno 1 - 10
of 1 221
pro vyhledávání: '"Nguyen Thanh TUNG"'
Autor:
Dwivedi, Vijay Prakash, Schlegel, Viktor, Liu, Andy T., Nguyen, Thanh-Tung, Kashyap, Abhinav Ramesh, Wei, Jeng, Yin, Wei-Hsian, Winkler, Stefan, Tan, Robby T.
Large Language Models (LLMs) have demonstrated remarkable performance across various domains, including healthcare. However, their ability to effectively represent structured non-textual data, such as the alphanumeric medical codes used in records li
Externí odkaz:
http://arxiv.org/abs/2410.13351
Autor:
Binici, Kuluhan, Kashyap, Abhinav Ramesh, Schlegel, Viktor, Liu, Andy T., Dwivedi, Vijay Prakash, Nguyen, Thanh-Tung, Gao, Xiaoxue, Chen, Nancy F., Winkler, Stefan
Automatic Speech Recognition (ASR) systems are pivotal in transcribing speech into text, yet the errors they introduce can significantly degrade the performance of downstream tasks like summarization. This issue is particularly pronounced in clinical
Externí odkaz:
http://arxiv.org/abs/2408.14418
Autor:
Nagar, Aishik, Schlegel, Viktor, Nguyen, Thanh-Tung, Li, Hao, Wu, Yuping, Binici, Kuluhan, Winkler, Stefan
Large Language Models (LLMs) are increasingly adopted for applications in healthcare, reaching the performance of domain experts on tasks such as question answering and document summarisation. Despite their success on these tasks, it is unclear how w
Externí odkaz:
http://arxiv.org/abs/2408.12249
Autor:
Subramanian, Anand, Schlegel, Viktor, Kashyap, Abhinav Ramesh, Nguyen, Thanh-Tung, Dwivedi, Vijay Prakash, Winkler, Stefan
There is vivid research on adapting Large Language Models (LLMs) to perform a variety of tasks in high-stakes domains such as healthcare. Despite their popularity, there is a lack of understanding of the extent and contributing factors that allow LLM
Externí odkaz:
http://arxiv.org/abs/2406.03699
Autor:
Schlegel, Viktor, Kashyap, Abhinav Ramesh, Nguyen, Thanh-Tung, Yang, Tsung-Han, Dwivedi, Vijay Prakash, Yin, Wei-Hsian, Wei, Jeng, Winkler, Stefan
Computerised clinical coding approaches aim to automate the process of assigning a set of codes to medical records. While there is active research pushing the state of the art on clinical coding for hospitalized patients, the outpatient setting -- wh
Externí odkaz:
http://arxiv.org/abs/2312.13533
Real-world weather conditions are intricate and often occur concurrently. However, most existing restoration approaches are limited in their applicability to specific weather conditions in training data and struggle to generalize to unseen weather ty
Externí odkaz:
http://arxiv.org/abs/2308.14334
Autor:
Nguyen-Ngoc, Khoi-Nguyen, Phan-Nguyen, Thanh-Tung, Le, Khanh-Duy, Nguyen, Tam V., Tran, Minh-Triet, Le, Trung-Nghia
The fashion e-commerce industry has witnessed significant growth in recent years, prompting exploring image-based virtual try-on techniques to incorporate Augmented Reality (AR) experiences into online shopping platforms. However, existing research h
Externí odkaz:
http://arxiv.org/abs/2308.13798
Autor:
Schlegel, Viktor, Li, Hao, Wu, Yuping, Subramanian, Anand, Nguyen, Thanh-Tung, Kashyap, Abhinav Ramesh, Beck, Daniel, Zeng, Xiaojun, Batista-Navarro, Riza Theresa, Winkler, Stefan, Nenadic, Goran
This paper describes PULSAR, our system submission at the ImageClef 2023 MediQA-Sum task on summarising patient-doctor dialogues into clinical records. The proposed framework relies on domain-specific pre-training, to produce a specialised language m
Externí odkaz:
http://arxiv.org/abs/2307.02006
Autor:
Li, Hao, Wu, Yuping, Schlegel, Viktor, Batista-Navarro, Riza, Nguyen, Thanh-Tung, Kashyap, Abhinav Ramesh, Zeng, Xiaojun, Beck, Daniel, Winkler, Stefan, Nenadic, Goran
Medical progress notes play a crucial role in documenting a patient's hospital journey, including his or her condition, treatment plan, and any updates for healthcare providers. Automatic summarisation of a patient's problems in the form of a problem
Externí odkaz:
http://arxiv.org/abs/2306.02754
Clinical notes in healthcare facilities are tagged with the International Classification of Diseases (ICD) code; a list of classification codes for medical diagnoses and procedures. ICD coding is a challenging multilabel text classification problem d
Externí odkaz:
http://arxiv.org/abs/2306.00005