Feb 23 (Reuters) - Eli Lilly (LLY.N), opens new tab said on Monday it received the U.S. Food and Drug Administration's approval to launch a four-dose KwikPen for its weight-loss drug Zepbound, ...

This is the first experiment of Image Segmentation for EndScopy Multi Organ Disease (EDD2020) based on our TensorFlowFlexUNet (TensorFlow Flexible UNet Image Segmentation Model for Multiclass), and an ...

Abstract: Distance-based unsupervised text classification is a method within text classification that leverages the semantic similarity between a label and a text to determine label relevance. This ...

A new family of Android click-fraud trojans leverages TensorFlow machine learning models to automatically detect and interact with specific advertisement elements. The mechanism relies on visual ...

Abstract: This paper proposes a multi-label text classification algorithm based on causal relationships to address the current challenge of accurately capturing label correlations in multi-label text ...

A meta-analysis of cohort studies assessing FLOT regimen in the treatment of esophageal cancer. Tislelizumab (TIS) + chemotherapy (CT) vs placebo (PBO) + CT as first-line treatment for locally ...

Dec 9 (Reuters) - Accenture (ACN.N), opens new tab and Anthropic on Tuesday announced an expansion of their partnership through a new business group where around 30,000 of the consulting giant's ...

The successful application of large-scale transformer models in Natural Language Processing (NLP) is often hindered by the substantial computational cost and data requirements of full fine-tuning.

A team of AI researchers at Bloomberg have developed PExA, an agentic framework that achieved 70.2% execution accuracy, sharing one of the top positions on the Spider 2.0 (Snow) leaderboard, one of ...

State Key Laboratory of Soil Pollution Control and Safety, and Women’s Hospital, School of Medicine, Zhejiang University, Hangzhou 310058, China ...

NeuralClassifier is designed for quick implementation of neural models for hierarchical multi-label classification task, which is more challenging and common in real-world scenarios. A salient feature ...