Extracting and analyzing relevant medical information from large-scale databases such as biobanks poses considerable challenges. To exploit such "big data," attempts have focused on large sampling ...

We developed two algorithms to identify patients with stomach, lung, colorectal, breast, and cervical cancers: diagnosis only (algorithm 1), and combining diagnosis, treatments, and medicines ...

Categorizing patients with cancer by their disease stage can be an important tool when conducting administrative claims-based studies. As claims databases frequently do not capture this information, ...

A research team has developed the SCAG algorithm for accurate branch detection and angle calculation in soybean plants using LiDAR data. SCAG achieved high accuracy in branch detection (F-score=0.77) ...