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Extreme Gradient Boosting (XGBoost) is an ML algorithm that improves model performance by using a series of decision trees, where each tree corrects the mistakes of the previous one. This sequential approach helps make predictions more accurate. Light Gradient-Boosting Machine (Light GBM) is another efficient algorithm that works similarly to XGBoost but is designed to be faster and more scalable, especially when working with large datasets and many features.
JMIR Cardio 2025;9:e68066
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Digital Mental Health Interventions for Young People Aged 16-25 Years: Scoping Review
J Med Internet Res 2025;27:e72892
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Cocreating the Visualization of Digital Mobility Outcomes: Delphi-Type Process With Patients
JMIR Form Res 2025;9:e68782
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Profile accuracy: H=high, M=medium, L=low. AUC: area under the curve; M: mixed; N: negative; P: positive; TPR: true-positive rate; TNR: true-negative rate.
The above summary (Figure 2) presents results for all pilot study patients to show performance and overall results. However, the individual prognostic patient profile as used in IMPT clinical assessment provides clearly presented summary results for each patient.
JMIR Rehabil Assist Technol 2025;12:e65890
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