Led by Professor Fu Jin, the study addresses a critical challenge in radiation therapy: balancing the computational speed and ...
A team of scientists from EPFL and Alaska Pacific University has developed an AI program that can recognize individual bears ...
Abstract: To tackle the challenge of data diversity in sentiment analysis and improve the accuracy and generalization ability of sentiment analysis, this study first cleans, denoises, and standardizes ...
Deep learning uses multi-layered neural networks that learn from data through predictions, error correction and parameter adjustments. It started with the ...
Deep learning has emerged as a transformative tool for the automated detection and classification of seizure events from intracranial EEG (iEEG) recordings. In this review, we synthesize recent ...
ABSTRACT: Liver cancer is one of the most prevalent and lethal forms of cancer, making early detection crucial for effective treatment. This paper introduces a novel approach for automated liver tumor ...
Abstract: The problem of UAV attack-defense confrontation is a hot research direction in the field of unmanned systems at present. However, in an environment with threat areas or obstacles, when the ...
ABSTRACT: Lung cancer stands as the preeminent cause of cancer-related mortality globally. Prompt and precise diagnosis, coupled with effective treatment, is imperative to reduce the fatality rates ...
Conclusions: Our findings demonstrate that compared with unimodal approaches, an integrated deep learning model incorporating both imaging and clinical data has greater diagnostic accuracy for MMP in ...
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