Tag: Machine Learning

A new leakage-audited benchmark shows that random data splitting inflates toxicity model performance by up to 0.079 AUROC points while ...

A real-world clinical validation of a commercial AI system for prostate MRI found high sensitivity for clinically significant cancer but ...

A new review maps how computational tools, from RNA folding algorithms to molecular dynamics simulations, are transforming the design of ...

A machine learning framework combining random forest prediction, neural network defect screening, and evolutionary optimization raised casting qualification rates to ...

A new study shows that machine learning models, particularly Support Vector Machines, predict the shear strength of recycled aggregate concrete ...

A machine learning study of 351 breast cancer patients shows that MRI radiomics features from both the tumor and its ...

Researchers in Pakistan have developed a real-time method that detects machine learning model drift in fog computing healthcare systems without ...

Researchers trained six machine learning models on 2,048 laboratory records and found gradient boosting predicts the compressive strength of cement-free ...

Researchers used machine learning, docking, and molecular dynamics to transform Traditional Chinese Medicine compounds into optimized computational leads against E. ...

A systematic review of 237 studies from 2014 to 2024 maps how explainable AI techniques such as SHAP and LIME ...

Researchers have built a whole-body computational model that simulates how vaccination site, timing, and tumor-derived suppression shape anti-cancer immune responses, ...

A new survey in Cluster Computing examines how deep reinforcement learning can manage mobility and preserve quality of service for ...

A new probabilistic and machine learning framework maps how climate change will accelerate carbonation-induced reinforcement corrosion across Brazil, revealing sharp ...

Researchers in China have developed FullReg, a semi-supervised regression framework that weights pseudo-labels by data similarity and stabilizes training with ...

A new open-source simulator called FLInterrupt makes sudden client dropouts a controllable experimental variable in federated learning research, revealing how ...

In recent years, artificial intelligence and machine learning have rapidly transformed numerous sectors, including healthcare. One of the most promising ...

Recent advancements in bioinformatics have led to the development of innovative models aimed at enhancing our understanding of post-translational modifications ...

In the realm of clinical proteomics, innovative tools are crucial for harnessing the vast amounts of proteomic data generated in ...

In the rapidly evolving field of robotics, maintaining seamless communication among multiple robotic units is paramount. The latest research by ...

In a groundbreaking study that merges technology and health sciences, researchers in China have employed machine learning methodologies to accurately ...