arXiv:2606. 19371v1 Announce Type: cross Abstract: Alzheimer's disease (AD) is a fatal disorder that destroys memory and cognitive skills in the elderly population.
By Long Doan, Branden Chen, Ethan Litton, Huan Huang, Jiajing Huang, Yixin Xie, Weihua Zhou, Nandakumar Narayanan, Chen Zhao
The paper introduces MCNet, a neural network that assigns a Modality Contribution Score (MCS) to each patient, indicating how much structural MRI versus amyloid PET drives the diagnostic decision for Alzheimer’s disease. Across 327 ADNI-3 participants, MCNet achieved strong three‑class staging (AUC = 0.881) and the MCS showed a clear, statistically significant increase in PET dominance from cognitively normal to AD. The method was validated on an independent OASIS‑3 cohort and compared favorably to SHAP, suggesting it can guide personalized imaging and clinical trial decisions.
By Dawa Chyophel Lepcha, Aaliya Ali, Sophie A. Martin, Deepika Koundal, Pierrick Coupe, Shabbir Syed-Abdul
arXiv:2607. 17442v1 Announce Type: new Abstract: Background.
By Navin Bondade
The paper introduces OPAL, a held‑out decision test that evaluates follow‑up measurement rules in biological screens by freezing a rule and assessing unnecessary measurement, coverage, and value after cost against pre‑defined archive‑specific criteria. Using a six‑rule Cell Painting battery, the authors show that a high‑value rule would re‑image 96.01% of the library with a 97.14% false‑activation upper bound, illustrating that predicted value alone cannot justify replacing a fixed plan. In development, a sparse Cell Painting rule reduced added‑well burden 18.2‑fold but had a false‑discovery bound above 35%, leading the fixed plan to remain; similar analyses for LINCS–LJP and CTRP highlighted the need for fallback strategies and the importance of separating optimization from evidence.
"whyItMatters":"OPAL provides a systematic way to determine whether a new measurement strategy truly improves experimental efficiency without compromising data quality, as demonstrated across multiple biological screening datasets."
By Jia Bi, Samuel Pinilla, Chenyang Zhu
arXiv:2610. 01278v1 Announce Type: new Abstract: Alzheimer's disease (AD) diagnosis requires sequential evidence acquisition under heterogeneous test costs and patient burden.
By Ziwen Yu, Ivan Koychev, Elizabeth Coulthard, Ting Zhou, Bolin Chen, Dian Hong, Zinuo You, Yujiao Wang, Anthony Mulholland, Qiang Liu
The paper introduces Observation‑Anchored Selective Assimilation (OASA) for forecasting tumor‑state proxies in post‑treatment glioma patients using serial MRI observations. OASA anchors the patient‑specific state with an intermediate observation and selectively updates it via a tiered rule and voxel‑wise soft gate, outperforming baseline methods in Dice score at certain thresholds. The approach is validated on 120 patient triplets and the code is publicly released.
By Yeonjae Jung, Minwoo Shin