533 citations · 533 across the 2 of their papers we have counts for
2 papers
stat.ME2024
Double trouble: Predicting new variant counts across two heterogeneous populations
Yunyi Shen, Lorenzo Masoero, Joshua G. Schraiber +1
Collecting genomics data across multiple heterogeneous populations (e.g., across different cancer types) has the potential to improve our understanding of disease. Despite sequenci…
stat.AP2020★ 533 cited
The importance of transparency and reproducibility in artificial intelligence research
Benjamin Haibe-Kains, George Alexandru Adam, Ahmed Hosny +17
In their study, McKinney et al. showed the high potential of artificial intelligence for breast cancer screening. However, the lack of detailed methods and computer code undermines…