Uncertainty Quantification on Clinical Trial Outcome Prediction

1 code implementation • 7 Jan 2024 • Tianyi Chen, Yingzhou Lu, Nan Hao, Yuanyuan Zhang, 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 +3

GenoCraft: A Comprehensive, User-Friendly Web-Based Platform for High-Throughput Omics Data Analysis and Visualization

1 code implementation • 21 Dec 2023 • Yingzhou Lu, Minjie Shen, Ling Yue, Chenhao Li, Lulu Chen, Fan Meng, Xiao Wang, David Herrington, Yue Wang, Yue Zhao, Tianfan Fu, Capucine van Rechem

With GenoCraft, researchers and data scientists have access to an array of cutting-edge bioinformatics tools under a user-friendly interface, making it a valuable resource for managing and analyzing large-scale omics data.

Machine Learning for Synthetic Data Generation: A Review

no code implementations • 8 Feb 2023 • Yingzhou Lu, Minjie Shen, Huazheng Wang, Xiao Wang, Capucine van Rechem, Tianfan Fu, Wenqi Wei

In light of these challenges, the concept of synthetic data generation emerges as a promising alternative that allows for data sharing and utilization in ways that real-world data cannot facilitate.

Fairness Synthetic Data Generation