Integrating deep learning with traditional forecasting techniques can improve early warning systems by capitalizing on each ...
Abstract: An electrocardiogram (ECG) is a non-invasive and cost-effective method for diagnosing heart disease. However, physicians often face challenges in interpreting ECG. As a result, deep learning ...
Abstract: This paper proposes a hybrid deep learning model integrating DenseNet201 and InceptionV3 to address the challenges in achieving accurate and reliable cervical cancer classification. Current ...
WiMi Hologram Cloud Inc. (NASDAQ: WiMi) ("WiMi" or the "Company"), a leading global Hologram Augmented Reality ("AR") ...
Denver, CO, Feb. 17, 2026 (GLOBE NEWSWIRE) -- GeoCue will unveil four new add-ons for its LP360 Drone point cloud processing software at Geo Week 2026 in Denver: AI Ground+, AI Forestry, AI Utilities ...
Lung cancer remains the leading cause of cancer-related mortality worldwide. Early detection of pulmonary nodules is crucial for timely diagnosis and effective treatment.
Li and colleagues developed a deep-learning model to analyze EEG recordings and detect event-level EEG spikes. 2. The model achieved high accuracy and a low false-positive rate, with only 32% of human ...
The proposed CNN-based system demonstrates the feasibility and robustness of deep learning for automatic lung nodule detection and classification. Despite strong results, the study acknowledges ...
High school students gain PhD-led mentorship, publish original research, and build real-world AI models through ...
Cal State Monterey Bay has earned the 2026 Carnegie Community Engagement Classification. The classification, awarded by the Carnegie Foundation for the Advancement of Teaching and the American Council ...
Researchers have significantly enhanced an artificial intelligence tool used to rapidly detect bacterial contamination in food by eliminating misclassifications of food debris that looks like bacteria ...
Head and neck cancer (HNC) is one of the most common malignancies worldwide, with high morbidity and mortality rates.