4 citations · 4 across the 4 of their papers we have counts for
4 papers
GC-MoE: Genomics-Guided Cell-Type-Specific Mixture of Experts for Histology-Based Single-Cell Spatial Transcriptomics
Kaito Shiku, Ahtisham Fazeel Abbasi, Ryoma Bise +4
Histology-based single-cell spatial transcriptomics (ST) estimation aims to predict gene expression for individual cells from histopathological images and cell locations, reducing…
A Large-Scale Comparative Analysis of Imputation Methods for Single-Cell RNA Sequencing Data
Yuichiro Iwashita, Ahtisham Fazeel Abbasi, Koichi Kise +2
Background: Single-cell RNA sequencing (scRNA-seq) enables gene expression profiling at cellular resolution but is inherently affected by sparsity caused by dropout events, where e…
CDMT-EHR: A Continuous-Time Diffusion Framework for Generating Mixed-Type Time-Series Electronic Health Records
Shaonan Liu, Yuichiro Iwashita, Soichiro Nakako +2
Electronic health records (EHRs) are invaluable for clinical research, yet privacy concerns severely restrict data sharing. Synthetic data generation offers a promising solution, b…
Had enough of experts? Quantitative knowledge retrieval from large language models
David Selby, Kai Spriestersbach, Yuichiro Iwashita +6
Large language models (LLMs) have been extensively studied for their abilities to generate convincing natural language sequences, however their utility for quantitative information…