4 papers
RosettaSearch: Multi-Objective Inference-Time Search for Protein Sequence Design
Meghana Kshirsagar, Allen Nie, Ching-An Cheng +5
We introduce RosettaSearch, an inference-time multi-objective optimization approach for backbone conditioned protein sequence design. We use large language models (LLMs) as a gener…
Towards reliable use of artificial intelligence to classify otitis media using otoscopic images: Addressing bias and improving data quality
Yixi Xu, Al-Rahim Habib, Graeme Crossland +8
Ear disease contributes significantly to global hearing loss, with recurrent otitis media being a primary preventable cause in children, impacting development. Artificial intellige…
Comprehensive framework for evaluation of deep neural networks in detection and quantification of lymphoma from PET/CT images: clinical insights, pitfalls, and observer agreement analyses
Shadab Ahamed, Yixi Xu, Sara Kurkowska +13
This study addresses critical gaps in automated lymphoma segmentation from PET/CT images, focusing on issues often overlooked in existing literature. While deep learning has been a…
Pytorch-Wildlife: A Collaborative Deep Learning Framework for Conservation
Andres Hernandez, Zhongqi Miao, Luisa Vargas +4
The alarming decline in global biodiversity, driven by various factors, underscores the urgent need for large-scale wildlife monitoring. In response, scientists have turned to auto…