In this study, we compared multiple machine learning algorithms and demonstrated, for the first time, the significant advantage of the XGBoost model in predicting 6-month HICH prognosis (AUC = 0.921 ...

Objective Early prediction of long-term outcomes in patients with systemic lupus erythematosus (SLE) remains a great challenge in clinical practice. Our study aims to develop and validate predictive ...

Long-read sequencing technologies analyze long, continuous stretches of DNA. These methods have the potential to improve researchers' ability to detect complex genetic alterations in cancer genomes.

SAVANA uses a machine learning algorithm to identify cancer-specific structural variations and copy number aberrations in long-read DNA sequencing data. The complex structure of cancer genomes ...

The paper offers up 13 areas where machine learning can be deployed, including energy production, CO 2 removal, education, solar geoengineering, and finance.Within these fields, the possibilities ...

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The inert gases Xe and Kr mainly exist in the used nuclear fuel (UNF) with the Xe/Kr ratio of 20:80, which it is difficult to separate. In this work, based on the G-MOFs database, high-throughput ...

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This project applies various machine learning models—especially XGBoost—to classify ECG heartbeat signals from the MIT-BIH Arrhythmia Database. Advanced metaheuristic optimization algorithms are used ...