12 citations · 34 across the 13 of their papers we have counts for
18 papers
From Retrieval to Reasoning: Agentic Mechanism Prediction from Cell Painting Profiles
Jiayuan Chen, Botao Yu, Tianyu Liu +3
Cell Painting is a high-content morphological profiling assay widely used for phenotype-based biological inference, with mechanism of action (MOA) prediction as a central applicati…
The Boundaries of Fair AI in Medical Image Prognosis: A Causal Perspective
Thai-Hoang Pham, Jiayuan Chen, Seungyeon Lee +4
As machine learning (ML) algorithms are increasingly used in medical image analysis, concerns have emerged about their potential biases against certain social groups. Although many…
SepsisCalc: Integrating Clinical Calculators into Early Sepsis Prediction via Dynamic Temporal Graph Construction
Changchang Yin, Shihan Fu, Bingsheng Yao +5
Sepsis is an organ dysfunction caused by a deregulated immune response to an infection. Early sepsis prediction and identification allow for timely intervention, leading to improve…
Open-Set Heterogeneous Domain Adaptation: Theoretical Analysis and Algorithm
Thai-Hoang Pham, Yuanlong Wang, Changchang Yin +2
Domain adaptation (DA) tackles the issue of distribution shift by learning a model from a source domain that generalizes to a target domain. However, most existing DA methods are d…
Non-stationary Domain Generalization: Theory and Algorithm
Thai-Hoang Pham, Xueru Zhang, Ping Zhang
Although recent advances in machine learning have shown its success to learn from independent and identically distributed (IID) data, it is vulnerable to out-of-distribution (OOD)…
Domain Invariant Representation Learning and Sleep Dynamics Modeling for Automatic Sleep Staging
Seungyeon Lee, Thai-Hoang Pham, Zhao Cheng +1
Sleep staging has become a critical task in diagnosing and treating sleep disorders to prevent sleep related diseases. With growing large scale sleep databases, significant progres…
Fairness and Accuracy under Domain Generalization
Thai-Hoang Pham, Xueru Zhang, Ping Zhang
As machine learning (ML) algorithms are increasingly used in high-stakes applications, concerns have arisen that they may be biased against certain social groups. Although many app…
Cardiac Complication Risk Profiling for Cancer Survivors via Multi-View Multi-Task Learning
Thai-Hoang Pham, Changchang Yin, Laxmi Mehta +2
Complication risk profiling is a key challenge in the healthcare domain due to the complex interaction between heterogeneous entities (e.g., visit, disease, medication) in clinical…
TransICD: Transformer Based Code-wise Attention Model for Explainable ICD Coding
Biplob Biswas, Thai-Hoang Pham, Ping Zhang
International Classification of Disease (ICD) coding procedure which refers to tagging medical notes with diagnosis codes has been shown to be effective and crucial to the billing…
Multi-Task Learning with Contextualized Word Representations for Extented Named Entity Recognition
Thai-Hoang Pham, Khai Mai, Nguyen Minh Trung +4
Fine-Grained Named Entity Recognition (FG-NER) is critical for many NLP applications. While classical named entity recognition (NER) has attracted a substantial amount of research,…
Vietnamese Semantic Role Labelling
Phuong Le-Hong, Thai Hoang Pham, Xuan Khoai Pham +3
In this paper, we study semantic role labelling (SRL), a subtask of semantic parsing of natural language sentences and its application for the Vietnamese language. We present our e…
On the Use of Machine Translation-Based Approaches for Vietnamese Diacritic Restoration
Thai-Hoang Pham, Xuan-Khoai Pham, Phuong Le-Hong
This paper presents an empirical study of two machine translation-based approaches for Vietnamese diacritic restoration problem, including phrase-based and neural-based machine tra…
An Empirical Study of Discriminative Sequence Labeling Models for Vietnamese Text Processing
Phuong Le-Hong, Minh Pham Quang Nhat, Thai-Hoang Pham +2
This paper presents an empirical study of two widely-used sequence prediction models, Conditional Random Fields (CRFs) and Long Short-Term Memory Networks (LSTMs), on two fundament…
NNVLP: A Neural Network-Based Vietnamese Language Processing Toolkit
Thai-Hoang Pham, Xuan-Khoai Pham, Tuan-Anh Nguyen +1
This paper demonstrates neural network-based toolkit namely NNVLP for essential Vietnamese language processing tasks including part-of-speech (POS) tagging, chunking, named entity…
Building a Semantic Role Labelling System for Vietnamese
Thai-Hoang Pham, Xuan-Khoai Pham, Phuong Le-Hong
Semantic role labelling (SRL) is a task in natural language processing which detects and classifies the semantic arguments associated with the predicates of a sentence. It is an im…
Content-based Approach for Vietnamese Spam SMS Filtering
Thai-Hoang Pham, Phuong Le-Hong
Short Message Service (SMS) spam is a serious problem in Vietnam because of the availability of very cheap pre-paid SMS packages. There are some systems to detect and filter spam m…
The Importance of Automatic Syntactic Features in Vietnamese Named Entity Recognition
Thai-Hoang Pham, Phuong Le-Hong
This paper presents a state-of-the-art system for Vietnamese Named Entity Recognition (NER). By incorporating automatic syntactic features with word embeddings as input for bidirec…
End-to-end Recurrent Neural Network Models for Vietnamese Named Entity Recognition: Word-level vs. Character-level
Thai-Hoang Pham, Phuong Le-Hong
This paper demonstrates end-to-end neural network architectures for Vietnamese named entity recognition. Our best model is a combination of bidirectional Long Short-Term Memory (Bi…