AI is revolutionizing the IVD market by enhancing diagnostic accuracy and speed. Key opportunities lie in AI integration across workflows, cloud solutions, regulatory support, and supply chain ...

A research team has developed a powerful unsupervised deep learning network that can accurately separate wood and leaf ...

Abstract: By using labeled source domain data to train supervised models, unsupervised domain adapted (UDA) semantic segmentation tries to produce precise predictions in the unlabeled target domain.

Artificial intelligence (AI) is rapidly transforming how scientific research is conducted, from accelerating model development to uncovering novel drug discovery pathways. However, with every promise ...

In recent years, the development of autonomous AI agents capable of independently building and deploying code has gained ...

According to the latest information from the National Intellectual Property Administration, Hangzhou Zhisi Da Technology Co., Ltd. applied for a patent titled "An AI Visual Inspection Method Based on ...

Presentation of the best paper award at the RoboCup 2025 symposium. An important aspect of autonomous soccer-playing robots concerns accurate detection of the ball. This is the focus of work by Can ...

Supervised Machine Learning Models for Predicting Sepsis-Associated Liver Injury in Patients With Sepsis: Development and Validation Study Based on a Multicenter Cohort Study ...

Abstract: Unsupervised learning visible-infrared person re-identification (USL-VI-ReID) aims to learn modality-invariant features from unlabeled cross-modality data. However, existing approaches lack ...

Traditional cardiovascular risk assessment entails investigator‐defined exposure levels and individual risk markers in multivariable analysis. We sought to determine whether an alternative unbiased ...