6k citations
- Harvard UniversityUS93 papers
- Brigham and Women's HospitalUS54 papers
- Northeastern UniversityUS39 papers
- Dana-Farber/Harvard Cancer CenterUS23 papers
- Dana-Farber Brigham Cancer CenterUS21 papers
- Massachusetts Institute of TechnologyUS17 papers
- Broad InstituteUS10 papers
- Massachusetts General HospitalUS8 papers
- Peking UniversityCN8 papers
- University of CambridgeGB8 papers
- University of Notre DameUS7 papers
- Budapest University of Technology and EconomicsHU6 papers
137 papers
Do Pathology Foundation Models Encode Disease Progression? A Pseudotime Analysis of Visual Representations
Pritika Vig, Ren-Chin Wu, William Lotter
Vision foundation models trained on discretely sampled images achieve strong performance on classification benchmarks, yet whether their representations encode the continuous proce…
Coclique level structure for stochastic chemical reaction networks
Simone Bruno, Yi Fu, Felipe A. Campos +2
Continuous time Markov chains are commonly used as models for the stochastic behavior of chemical reaction networks. More precisely, these Stochastic Chemical Reaction Networks (SC…
Cognitive bias in LLM reasoning compromises interpretation of clinical oncology notes
Matthew W. Kenaston, Umair Ayub, Mihir Parmar +14
Despite high performance on clinical benchmarks, large language models may reach correct conclusions through faulty reasoning, a failure mode with safety implications for oncology…
Finding easy regions for short-read variant calling from pangenome data
Heng Li
Background: While benchmarks on short-read variant calling suggest low error rate below 0.5%, they are only applicable to predefined confident regions. For a human sample without s…
BWT construction and search at the terabase scale
Heng Li
Motivation: Burrows-Wheeler Transform (BWT) is a common component in full-text indices. Initially developed for data compression, it is particularly powerful for encoding redundant…
On the Hardness of Measuring Magic
Roy J. Garcia, Gaurav Bhole, Kaifeng Bu +3
Quantum computers promise to solve computational problems significantly faster than classical computers. These 'speed-ups' are achieved by utilizing a resource known as magic. Meas…