Most mainstream methods rely on fingerprints or graph-based feature extraction, the emergence of large language models (LLMs) offers new prospects for molecular representation learning in toxicity ...

Using Real-World Data for Machine-Learning Algorithms to Predict the Treatment Response in Advanced Melanoma: A Pilot Study for Personalizing Cancer Care This study aims to investigate the impact of ...

Abstract: A neural network (NN) is developed to predict the elastic properties of reservoirs from acoustic data acquired during logging. The NN is applied to flexural and quadrupole slowness curves ...

A Nature Medicine paper by City of Hope and Memorial Sloan Kettering (MSK) Cancer Center outlines a new tool that measures blood inflammation as a marker for poor CAR T therapy outcomes CAR T cell ...

A recent study by Yale researchers demonstrated the potential of a machine learning approach to predict symptoms of post-traumatic stress disorder, or PTSD, for recent trauma survivors. Researchers ...

At the University of Guelph, my research team and I are working on AI solutions to help track and predict the avian influenza outbreaks. Our research — which is currently under review — has ...

A research team has successfully developed a technology that utilizes Large Language Models (LLMs) to predict the synthesizability ... success rates. While machine learning models have been ...

The prediction of candidate drugs targeting the feature genes ... offering new insights into the molecular mechanisms underlying the disease and paving the way for targeted interventions. The authors ...