Search Results for author: Jintai Chen

Found 43 papers, 21 papers with code

Protein-Mamba: Biological Mamba Models for Protein Function Prediction

no code implementations22 Sep 2024 Bohao Xu, Yingzhou Lu, Yoshitaka Inoue, Namkyeong Lee, Tianfan Fu, Jintai Chen

Protein function prediction is a pivotal task in drug discovery, significantly impacting the development of effective and safe therapeutics.

Drug Discovery Mamba +2

Quantum-inspired Reinforcement Learning for Synthesizable Drug Design

no code implementations13 Sep 2024 Dannong Wang, Jintai Chen, Zhiding Liang, Tianfan Fu, Xiao-Yang Liu

To address this issue, in this paper, we introduce a novel approach using the reinforcement learning method with quantum-inspired simulated annealing policy neural network to navigate the vast discrete space of chemical structures intelligently.

Drug Discovery Navigate +2

Quantum-machine-assisted Drug Discovery: Survey and Perspective

no code implementations24 Aug 2024 Yidong Zhou, Jintai Chen, Jinglei Cheng, Gopal Karemore, Marinka Zitnik, Frederic T. Chong, Junyu Liu, Tianfan Fu, Zhiding Liang

Drug discovery and development is a highly complex and costly endeavor, typically requiring over a decade and substantial financial investment to bring a new drug to market.

Drug Discovery Survey

Cross-composition Feature Disentanglement for Compositional Zero-shot Learning

no code implementations19 Aug 2024 Yuxia Geng, Runkai Zhu, Jiaoyan Chen, Jintai Chen, Zhuo Chen, Xiang Chen, Can Xu, Yuxiang Wang, Xiaoliang Xu

Disentanglement of visual features of primitives (i. e., attributes and objects) has shown exceptional results in Compositional Zero-shot Learning (CZSL).

Attribute Compositional Zero-Shot Learning +2

TeleOR: Real-time Telemedicine System for Full-Scene Operating Room

no code implementations29 Jul 2024 Yixuan Wu, Kaiyuan Hu, Qian Shao, Jintai Chen, Danny Z. Chen, Jian Wu

The advent of telemedicine represents a transformative development in leveraging technology to extend the reach of specialized medical expertise to remote surgeries, a field where the immediacy of expert guidance is paramount.

Multi-Modal CLIP-Informed Protein Editing

no code implementations27 Jul 2024 Mingze Yin, Hanjing Zhou, Yiheng Zhu, Miao Lin, Yixuan Wu, Jialu Wu, Hongxia Xu, Chang-Yu Hsieh, Tingjun Hou, Jintai Chen, Jian Wu

Proteins govern most biological functions essential for life, but achieving controllable protein discovery and optimization remains challenging.

Attribute Contrastive Learning

TrialEnroll: Predicting Clinical Trial Enrollment Success with Deep & Cross Network and Large Language Models

no code implementations18 Jul 2024 Ling Yue, Sixue Xing, Jintai Chen, Tianfan Fu

Clinical trials need to recruit a sufficient number of volunteer patients to demonstrate the statistical power of the treatment (e. g., a new drug) in curing a certain disease.

Language Modelling Large Language Model +1

Team up GBDTs and DNNs: Advancing Efficient and Effective Tabular Prediction with Tree-hybrid MLPs

1 code implementation13 Jul 2024 Jiahuan Yan, Jintai Chen, Qianxing Wang, Danny Z. Chen, Jian Wu

In our framework, a tensorized, rapidly trained GBDT feature gate, a DNN architecture pruning approach, as well as a vanilla back-propagation optimizer collaboratively train a randomly initialized MLP model.

Model Selection

TrialBench: Multi-Modal Artificial Intelligence-Ready Clinical Trial Datasets

1 code implementation30 Jun 2024 Jintai Chen, Yaojun Hu, Yue Wang, Yingzhou Lu, Xu Cao, Miao Lin, Hongxia Xu, Jian Wu, Cao Xiao, Jimeng Sun, Lucas Glass, Kexin Huang, Marinka Zitnik, Tianfan Fu

Clinical trials are pivotal for developing new medical treatments, yet they typically pose some risks such as patient mortality, adverse events, and enrollment failure that waste immense efforts spanning over a decade.

What is the Visual Cognition Gap between Humans and Multimodal LLMs?

1 code implementation14 Jun 2024 Xu Cao, Bolin Lai, Wenqian Ye, Yunsheng Ma, Joerg Heintz, Jintai Chen, Jianguo Cao, James M. Rehg

Recently, Multimodal Large Language Models (MLLMs) have shown great promise in language-guided perceptual tasks such as recognition, segmentation, and object detection.

object-detection Object Detection +2

Cross-Table Pretraining towards a Universal Function Space for Heterogeneous Tabular Data

no code implementations1 Jun 2024 Jintai Chen, Zhen Lin, Qiyuan Chen, Jimeng Sun

Yet, when applied to tabular data prediction, this paradigm faces challenges due to the limited reusable patterns among diverse tabular datasets (tables) and the general scarcity of tabular data available for fine-tuning.

ClinicalAgent: Clinical Trial Multi-Agent System with Large Language Model-based Reasoning

no code implementations23 Apr 2024 Ling Yue, Sixue Xing, Jintai Chen, Tianfan Fu

Large Language Models (LLMs) and multi-agent systems have shown impressive capabilities in natural language tasks but face challenges in clinical trial applications, primarily due to limited access to external knowledge.

Language Modelling Large Language Model

TrialDura: Hierarchical Attention Transformer for Interpretable Clinical Trial Duration Prediction

no code implementations20 Apr 2024 Ling Yue, Jonathan Li, Sixue Xing, Md Zabirul Islam, Bolun Xia, Tianfan Fu, Jintai Chen

The clinical trial process, a critical phase in drug development, is essential for developing new treatments.

Group-On: Boosting One-Shot Segmentation with Supportive Query

no code implementations18 Apr 2024 Hanjing Zhou, Mingze Yin, Jintai Chen, Danny Chen, Jian Wu

One-shot semantic segmentation aims to segment query images given only ONE annotated support image of the same class.

One-Shot Segmentation Segmentation

Personalized Heart Disease Detection via ECG Digital Twin Generation

1 code implementation17 Apr 2024 Yaojun Hu, Jintai Chen, Lianting Hu, Dantong Li, Jiahuan Yan, Haochao Ying, Huiying Liang, Jian Wu

Heart diseases rank among the leading causes of global mortality, demonstrating a crucial need for early diagnosis and intervention.

Management

Multi-rater Prompting for Ambiguous Medical Image Segmentation

no code implementations11 Apr 2024 Jinhong Wang, Yi Cheng, Jintai Chen, Hongxia Xu, Danny Chen, Jian Wu

In this paper, we tackle two challenges arisen in multi-rater annotations for medical image segmentation (called ambiguous medical image segmentation): (1) How to train a deep learning model when a group of raters produces a set of diverse but plausible annotations, and (2) how to fine-tune the model efficiently when computation resources are not available for re-training the entire model on a different dataset domain.

Image Segmentation Medical Image Segmentation +2

PoCo: A Self-Supervised Approach via Polar Transformation Based Progressive Contrastive Learning for Ophthalmic Disease Diagnosis

1 code implementation28 Mar 2024 Jinhong Wang, Tingting Chen, Jintai Chen, Yixuan Wu, Yuyang Xu, Danny Chen, Haochao Ying, Jian Wu

In this paper, we present a self-supervised method via polar transformation based progressive contrastive learning, called PoCo, for ophthalmic disease diagnosis.

Contrastive Learning

LKM-UNet: Large Kernel Vision Mamba UNet for Medical Image Segmentation

2 code implementations12 Mar 2024 Jinhong Wang, Jintai Chen, Danny Chen, Jian Wu

In this paper, we introduce a Large Kernel Vision Mamba U-shape Network, or LKM-UNet, for medical image segmentation.

Image Segmentation Long-range modeling +3

Making Pre-trained Language Models Great on Tabular Prediction

1 code implementation4 Mar 2024 Jiahuan Yan, Bo Zheng, Hongxia Xu, Yiheng Zhu, Danny Z. Chen, Jimeng Sun, Jian Wu, Jintai Chen

Condensing knowledge from diverse domains, language models (LMs) possess the capability to comprehend feature names from various tables, potentially serving as versatile learners in transferring knowledge across distinct tables and diverse prediction tasks, but their discrete text representation space is inherently incompatible with numerical feature values in tables.

SERVAL: Synergy Learning between Vertical Models and LLMs towards Oracle-Level Zero-shot Medical Prediction

no code implementations3 Mar 2024 Jiahuan Yan, Jintai Chen, Chaowen Hu, Bo Zheng, Yaojun Hu, Jimeng Sun, Jian Wu

Recent development of large language models (LLMs) has exhibited impressive zero-shot proficiency on generic and common sense questions.

Common Sense Reasoning

Unraveling Babel: Exploring Multilingual Activation Patterns of LLMs and Their Applications

no code implementations26 Feb 2024 Weize Liu, Yinlong Xu, Hongxia Xu, Jintai Chen, Xuming Hu, Jian Wu

Through comprehensive experiments on different model families, different model sizes, and different variants, we analyzed the similarities and differences in the internal neuron activation patterns of LLMs when processing different languages.

Uncertainty Quantification on Clinical Trial Outcome Prediction

1 code implementation7 Jan 2024 Tianyi Chen, Yingzhou Lu, Nan Hao, Capucine van Rechem, Jintai Chen, Tianfan Fu

Selective classification, encompassing a spectrum of methods for uncertainty quantification, empowers the model to withhold decision-making in the face of samples marked by ambiguity or low confidence, thereby amplifying the accuracy of predictions for the instances it chooses to classify.

Decision Making Drug Discovery +2

A Survey on Multimodal Large Language Models for Autonomous Driving

1 code implementation21 Nov 2023 Can Cui, Yunsheng Ma, Xu Cao, Wenqian Ye, Yang Zhou, Kaizhao Liang, Jintai Chen, Juanwu Lu, Zichong Yang, Kuei-Da Liao, Tianren Gao, Erlong Li, Kun Tang, Zhipeng Cao, Tong Zhou, Ao Liu, Xinrui Yan, Shuqi Mei, Jianguo Cao, Ziran Wang, Chao Zheng

We first introduce the background of Multimodal Large Language Models (MLLMs), the multimodal models development using LLMs, and the history of autonomous driving.

Autonomous Driving

Mind's Mirror: Distilling Self-Evaluation Capability and Comprehensive Thinking from Large Language Models

1 code implementation15 Nov 2023 Weize Liu, Guocong Li, Kai Zhang, Bang Du, Qiyuan Chen, Xuming Hu, Hongxia Xu, Jintai Chen, Jian Wu

While techniques such as chain-of-thought (CoT) distillation have displayed promise in distilling LLMs into small language models (SLMs), there is a risk that distilled SLMs may still inherit flawed reasoning and hallucinations from LLMs.

Transfer Learning

TabCaps: A Capsule Neural Network for Tabular Data Classification with BoW Routing

1 code implementation ICLR 2023 Jintai Chen, Kuanlun Liao, Yanwen Fang, Danny Chen, Jian Wu

In this paper, we propose to encapsulate all feature values of a record into vectorial features and process them collectively rather than have to deal with individual ones, which directly captures the representations at the data level and benefits robust performances.

OneSeg: Self-learning and One-shot Learning based Single-slice Annotation for 3D Medical Image Segmentation

no code implementations24 Sep 2023 Yixuan Wu, Bo Zheng, Jintai Chen, Danny Z. Chen, Jian Wu

As deep learning methods continue to improve medical image segmentation performance, data annotation is still a big bottleneck due to the labor-intensive and time-consuming burden on medical experts, especially for 3D images.

Image Segmentation Medical Image Segmentation +5

GCL: Gradient-Guided Contrastive Learning for Medical Image Segmentation with Multi-Perspective Meta Labels

no code implementations16 Sep 2023 Yixuan Wu, Jintai Chen, Jiahuan Yan, Yiheng Zhu, Danny Z. Chen, Jian Wu

Since annotating medical images for segmentation tasks commonly incurs expensive costs, it is highly desirable to design an annotation-efficient method to alleviate the annotation burden.

Attribute Contrastive Learning +4

Ord2Seq: Regarding Ordinal Regression as Label Sequence Prediction

1 code implementation ICCV 2023 Jinhong Wang, Yi Cheng, Jintai Chen, Tingting Chen, Danny Chen, Jian Wu

In this way, we decompose an ordinal regression task into a series of recursive binary classification steps, so as to subtly distinguish adjacent categories.

Binary Classification regression

Cross-Layer Retrospective Retrieving via Layer Attention

1 code implementation8 Feb 2023 Yanwen Fang, Yuxi Cai, Jintai Chen, Jingyu Zhao, Guangjian Tian, Guodong Li

Motivated by this, we devise a cross-layer attention mechanism, called multi-head recurrent layer attention (MRLA), that sends a query representation of the current layer to all previous layers to retrieve query-related information from different levels of receptive fields.

Image Classification Instance Segmentation +3

ExcelFormer: A neural network surpassing GBDTs on tabular data

1 code implementation7 Jan 2023 Jintai Chen, Jiahuan Yan, Qiyuan Chen, Danny Ziyi Chen, Jian Wu, Jimeng Sun

In this paper, we delve into this question: Can we develop a deep learning model that serves as a "sure bet" solution for a wide range of tabular prediction tasks, while also being user-friendly for casual users?

Data Augmentation Model Selection

T2G-Former: Organizing Tabular Features into Relation Graphs Promotes Heterogeneous Feature Interaction

1 code implementation30 Nov 2022 Jiahuan Yan, Jintai Chen, Yixuan Wu, Danny Z. Chen, Jian Wu

Recent development of deep neural networks (DNNs) for tabular learning has largely benefited from the capability of DNNs for automatic feature interaction.

Relation

Robust Training of Graph Neural Networks via Noise Governance

1 code implementation12 Nov 2022 Siyi Qian, Haochao Ying, Renjun Hu, Jingbo Zhou, Jintai Chen, Danny Z. Chen, Jian Wu

To address these issues, we propose a novel RTGNN (Robust Training of Graph Neural Networks via Noise Governance) framework that achieves better robustness by learning to explicitly govern label noise.

Memorization

Identifying Electrocardiogram Abnormalities Using a Handcrafted-Rule-Enhanced Neural Network

1 code implementation16 Jun 2022 Yuexin Bian, Jintai Chen, Xiaojun Chen, Xiaoxian Yang, Danny Z. Chen, Jian Wu

Automatic ECG classification methods, especially the deep learning based ones, have been proposed to detect cardiac abnormalities using ECG records, showing good potential to improve clinical diagnosis and help early prevention of cardiovascular diseases.

Clinical Knowledge Deep Learning +1

D-Former: A U-shaped Dilated Transformer for 3D Medical Image Segmentation

1 code implementation3 Jan 2022 Yixuan Wu, Kuanlun Liao, Jintai Chen, Jinhong Wang, Danny Z. Chen, Honghao Gao, Jian Wu

In this paper, we propose a new method called Dilated Transformer, which conducts self-attention for pair-wise patch relations captured alternately in local and global scopes.

Decoder Image Segmentation +3

DANets: Deep Abstract Networks for Tabular Data Classification and Regression

1 code implementation6 Dec 2021 Jintai Chen, Kuanlun Liao, Yao Wan, Danny Z. Chen, Jian Wu

A special basic block is built using AbstLays, and we construct a family of Deep Abstract Networks (DANets) for tabular data classification and regression by stacking such blocks.

regression

Electrocardio Panorama: Synthesizing New ECG Views with Self-supervision

1 code implementation12 May 2021 Jintai Chen, Xiangshang Zheng, Hongyun Yu, Danny Z. Chen, Jian Wu

For the first time, we propose a new concept, Electrocardio Panorama, which allows visualizing ECG signals from any queried viewpoints.

Self-Supervised Learning

Doctor Imitator: Hand-Radiography-based Bone Age Assessment by Imitating Scoring Methods

no code implementations10 Feb 2021 Jintai Chen, Bohan Yu, Biwen Lei, Ruiwei Feng, Danny Z. Chen, Jian Wu

The architecture of DI is designed to learn the diagnostic logistics of doctors using the scoring methods (e. g., the Tanner-Whitehouse method) for bone age assessment.

Anatomy

Flow-Mixup: Classifying Multi-labeled Medical Images with Corrupted Labels

no code implementations9 Feb 2021 Jintai Chen, Hongyun Yu, Ruiwei Feng, Danny Z. Chen, Jian Wu

In clinical practice, medical image interpretation often involves multi-labeled classification, since the affected parts of a patient tend to present multiple symptoms or comorbidities.

Image Classification Medical Image Classification

A Hierarchical Graph Network for 3D Object Detection on Point Clouds

no code implementations CVPR 2020 Jintai Chen, Biwen Lei, Qingyu Song, Haochao Ying, Danny Z. Chen, Jian Wu

Next, a new GConv based Proposal Reasoning Module reasons on the proposals considering the global scene semantics, and the bounding boxes are then predicted.

3D Object Detection Object +1

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