Neural networks : the official journal of the International Neural Network Society
Sep 1, 2025
Anomaly detection in intelligent surveillance system is an important and challenging task, which commonly learns a model describing normal patterns via frame reconstruction or prediction and assumes that anomalies deviate form the learned normal mode...
Computer methods and programs in biomedicine
Sep 1, 2025
BACKGROUND AND OBJECTIVE: Despite the profound advancements that deep learning models have achieved across a multitude of domains, their propensity to learn spurious correlations significantly impedes their applicability to tasks necessitating causal...
RATIONALE AND OBJECTIVES: Early detection of malignant lesions in ultrasound images is crucial for effective cancer diagnosis and treatment. While traditional methods rely on radiologists, deep learning models can improve accuracy, reduce errors, and...
Neural networks : the official journal of the International Neural Network Society
Sep 1, 2025
Visual attention models aim to predict human gaze behavior, yet traditional saliency models and deep gaze prediction networks face limitations. Saliency models rely on handcrafted low-level visual features, often failing to capture human gaze dynamic...
The role of artificial intelligence (AI) in cancer drug discovery and development has garnered significant attention due to its potential to transform the traditionally time-consuming and expensive processes involved in bringing new therapies to mark...
BACKGROUND: Substantial gaps exist in the neuroprognostication of cardiac arrest patients who remain comatose after the restoration of spontaneous circulation. Most studies focus on predicting survival, a measure confounded by the withdrawal of life-...
RATIONALE AND OBJECTIVES: This study aims to develop and validate a deep learning radiomics signature (DLRS) that integrates radiomics and deep learning features for the non-invasive prediction of microvascular invasion (MVI) in patients with colon c...
Journal of the science of food and agriculture
Sep 1, 2025
BACKGROUND: Computer vision and the use of image-based solutions are gaining traction as non-destructive food assessment methods because of the low costs of computational equipment. Research conducted on the development of wheat classification models...
RATIONALE AND OBJECTIVES: The aim of this study is to develop a deep learning-based multimodal feature interaction-guided fusion (DL-MFIF) framework that integrates macroscopic information from computed tomography (CT) images with microscopic informa...
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.