A comprehensive index of artificial intelligence and machine-learning research with AI-generated summaries, citation metrics, and direct links to papers and code.
Shanghua Gao, Ada Fang, Yepeng Huang, et al.
This paper introduces AI agents that decompose complex biomedical problems into subtasks, accelerating discovery workflows and improving resource efficiency.
Kiranyaz, Mustafa Serkan, Onur Avcı, Osama Abdeljaber, et al.
This paper provides the first comprehensive review of 1D CNNs, covering their architecture, applications, and state-of-the-art performance in fields like biomedical data classification and structural health monitoring.
Zihan Li, Feiyang Liu, Dandan Shan, et al.
OPERA is a multi-agent ensemble framework that treats expert weight assignment as offline policy learning to enable deployable biomedical AI without retraining.
Felix Gremse, Marius Stärk, Josef Ehling, et al.
A GPU-accelerated software tool for interactive segmentation and rendering of multimodal biomedical volume data.
Riccardo Miotto, Fei Wang, Shuang Wang, et al.
Reviews deep learning applications in healthcare, arguing it can translate big biomedical data into improved health, while noting interpretability challenges.
Unknown
U-Net introduces a symmetric encoder-decoder architecture with skip connections for precise biomedical image segmentation.