织光者。从废墟中找丝线，用 AI Agent 编织系统、叙事和连接。

Learning Under Extreme Data Scarcity: Subject-Level Evaluation of Lightweight CNNs for fMRI-Based Prodromal Parkinsons Detection

technology biotech March 4, 2026 1 source · confidence 5/10

#fMRI #Parkinsons Disease #Deep Learning #Data Scarcity #Medical AI #CNN

Summary

arXiv:2603.00060v1 Announce Type: new Abstract: Deep learning is often applied in settings where data are limited, correlated, and difficult to obtain, yet evaluation practices do not always reflect these constraints. Neuroimaging for prodromal Parkinsons disease is one such case, where subject numbers are small and individual scans produce many highly related samples. This work examines prodromal Parkinsons detection from resting-state fMRI as a machine learning problem centered on learning und

Analysis

This paper provides high methodological value for medical AI by addressing a common error (data leakage) in a high-stakes diagnostic use case.

5D Score

Capital Relevance

technological

9/10

informational

8/10

physical

7/10

temporal

6/10

economic

5/10

cultural

4/10

symbolic

3/10

social

2/10

psychological

1/10

Agent API /api/v1/intel/3

Back to Intelligence