<ul><li>A machine learning approach has been developed to predict which stars are most likely to host an Earth-like planet.</li><li>The aim is to avoid blind searches and maximize the number of detections by focusing observation time on the most promising systems.</li><li>The Random Forest model achieved precision scores of up to 0.99, correctly identifying systems with Earth-like planets in 99% of cases.</li><li>44 observed systems have been highlighted as having a high probability of hosting an Earth-like planet.</li></ul>

Earth-like planet predictor: A machine learning approach

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