Biological domain shift and statistical nesting concerns in generative AI-based spatial tumor growth prediction for pediatric diffuse midline glioma.
Li W, Sun X, Pei S. · BMC medicine · 2026-08-12
对上述DMG生成模型的方法学批评。
标签：批评与反证
共 5 条，按时间倒序。
Systematic evaluation of single-cell foundation model interpretability: attention-derived edge scores add no incremental value over gene-level features for perturbation-target prediction.
Kendiukhov I. · BMC genomics · 2026-07-22
单细胞基础模型注意力边得分未增加调控网络信息。
Deep-learning-based gene perturbation effect prediction does not yet outperform simple linear baselines.
Ahlmann-Eltze C, Huber W, Anders S. · Nature methods · 2025-08-04
Ahlmann-Eltze等：深度模型未超越简单线性基线。
Benchmarking foundation cell models for post-perturbation RNA-seq prediction.
Csendes G, Sanz G, Szalay KZ, Szalai B. · BMC genomics · 2025-04-23
Csendes等：基础模型扰动预测不如简单基线。
Zero-shot evaluation reveals limitations of single-cell foundation models.
Kedzierska KZ, Crawford L, Amini AP, Lu AX. · Genome biology · 2025-04-18
Kedzierska等：零样本评估揭示单细胞基础模型局限。