박치현

전체 41건 중 11번부터 20번까지의 결과를 표시합니다.

2024

Article

Pseq2Sites: Enhancing protein sequence-based ligand binding-site prediction accuracy via the deep convolutional network and attention mechanism

Article

PIDiff: Physics informed diffusion model for protein pocket-specific 3D molecular generation

Article

DrDiff: Drug Response Prediction Through Controllable Diffusion-GE and Graph Attention Network

2023

Article

Machine-Learning Algorithms Using Systemic Inflammatory Markers to Predict the Oncologic Outcomes of Colorectal Cancer After Surgery

Article

ASO Visual Abstract: Machine Learning Algorithms Using Systemic Inflammatory Markers for Predicting the Oncological Outcomes of Colorectal Cancer After Surgery

Article

Evaluation of nutritional status and clinical depression classification using an explainable machine learning method

Article

ReBADD-SE: Multi-objective molecular optimisation using SELFIES fragment and off-policy self-critical sequence training

Article

Improving Data Sparsity in Recommender Systems Using Matrix Regeneration with Item Features

2022

Article

톰슨 샘플링 기반의 신약 후보 물질 디자인을 위한 심층 생성 모델

Article

Predicting progression to dementia with "comprehensive visual rating scale" and machine learning algorithms

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Pseq2Sites: Enhancing protein sequence-based ligand binding-site prediction accuracy via the deep convolutional network and attention mechanism

PIDiff: Physics informed diffusion model for protein pocket-specific 3D molecular generation

DrDiff: Drug Response Prediction Through Controllable Diffusion-GE and Graph Attention Network

Machine-Learning Algorithms Using Systemic Inflammatory Markers to Predict the Oncologic Outcomes of Colorectal Cancer After Surgery

ASO Visual Abstract: Machine Learning Algorithms Using Systemic Inflammatory Markers for Predicting the Oncological Outcomes of Colorectal Cancer After Surgery

Evaluation of nutritional status and clinical depression classification using an explainable machine learning method

ReBADD-SE: Multi-objective molecular optimisation using SELFIES fragment and off-policy self-critical sequence training

Improving Data Sparsity in Recommender Systems Using Matrix Regeneration with Item Features

톰슨 샘플링 기반의 신약 후보 물질 디자인을 위한 심층 생성 모델

Predicting progression to dementia with "comprehensive visual rating scale" and machine learning algorithms