Tag: Machine Learning

A meta-analysis of 40 studies covering 12,769 patients shows that radiomics-based models combining CT image features with clinical data can ...

A neuronavigation-guided study shows that continuous-time random walk diffusion MRI metrics closely track pathological heterogeneity and immune cell proportions in ...

A prospective Chinese cohort study links long-term exposure to mixtures of common air pollutants with the new onset of combined ...

Researchers have combined non-negative matrix factorization with multi-objective particle swarm optimization to create a community detection algorithm that achieves perfect ...

A new study finds that AI systems and large language models achieve at best 25 percent accuracy in diagnosing psoriasis ...

Researchers have built a machine learning framework with an interactive interface that estimates full unsaturated soil hydraulic conductivity curves in ...

Researchers in India have developed a hybrid security framework that combines swarm-optimized neural network intrusion detection with blockchain-based trust management ...

The first Europe-wide expert working group on artificial intelligence in mental health has launched at the ECNP Congress in Munich ...

Researchers in Seoul have rebuilt the classic extreme studentized deviate test into an online, self-tuning algorithm that detects anomalies in ...

Researchers have developed a two-stage attention-enhanced deep learning framework that segments breast lesions in ultrasound images before classifying them, achieving ...

A hybrid deep learning framework combining fuzzy preprocessing, bio-inspired feature selection and a novel Hopfield attention network predicts organic perovskite ...

Researchers have developed MAPLE, a black-box adversarial defense framework that jointly purifies adversarial images and recalibrates the classifier's decision margins ...

Researchers have developed a graph-based deep learning network that decodes imagined movements from EEG signals with accuracies of up to ...

Researchers at the University of Tokyo developed CYAN, a machine-learning method that extracts reaction rate constants from routine yield-optimization data, ...

Researchers in China have developed a label-free temporal weighting method that fuses multispectral drone imagery from three wheat growth stages, ...

Researchers in India combined µEDM drilling experiments on titanium with benchmarked machine learning models, explainable AI, and a surrogate-based inverse ...

Researchers at Anhui University have developed KVCB, a key-value cache merging method that compresses large language model memory by fusing ...

Researchers built an eight-variable machine learning model that predicts in-hospital mortality in patients with sepsis-related myocardial injury and validated its ...

A new Cluster Computing study using stroke prediction shows that federated learning in healthcare will fail unless it confronts severe ...

A dual-center study shows that a deep learning radiomics model applied to routine mammograms can noninvasively predict HER2-positive and HER2-low ...