The Use of Machine Learning for Inferencing the Effectiveness of a Rehabilitation Program for Orthopedic and Neurological Patients
Advance assessment of the potential functional improvement of patients undergoing a rehabilitation program is crucial in developing precision medicine tools and patient-oriented rehabilitation programs, as well as in better allocating resources in hospitals. In this work, we propose a novel approach...
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| Veröffentlicht in: | International journal of environmental research and public health 2023-04, Vol.20 (8), p.5575 |
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| creator | Santilli, Valter Mangone, Massimiliano Diko, Anxhelo Alviti, Federica Bernetti, Andrea Agostini, Francesco Palagi, Laura Servidio, Marila Paoloni, Marco Goffredo, Michela Infarinato, Francesco Pournajaf, Sanaz Franceschini, Marco Fini, Massimo Damiani, Carlo |
| description | Advance assessment of the potential functional improvement of patients undergoing a rehabilitation program is crucial in developing precision medicine tools and patient-oriented rehabilitation programs, as well as in better allocating resources in hospitals. In this work, we propose a novel approach to this problem using machine learning algorithms focused on assessing the modified Barthel index (mBI) as an indicator of functional ability. We build four tree-based ensemble machine learning models and train them on a private training cohort of orthopedic (OP) and neurological (NP) hospital discharges. Moreover, we evaluate the models using a validation set for each category of patients using root mean squared error (RMSE) as an absolute error indicator between the predicted mBI and the actual values. The best results obtained from the study are an RMSE of 6.58 for OP patients and 8.66 for NP patients, which shows the potential of artificial intelligence in predicting the functional improvement of patients undergoing rehabilitation. |
| doi_str_mv | 10.3390/ijerph20085575 |
| format | Article |
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| subjects | Activities of Daily Living Algorithms Artificial Intelligence Computational linguistics Data mining Datasets Efficiency Hospitalization Hospitals Humans Intervention Language processing Learning algorithms Machine Learning Medical research Medicine, Experimental Missing data Natural language interfaces Orthopedics Patients Precision medicine Rehabilitation Root-mean-square errors Variables |
| title | The Use of Machine Learning for Inferencing the Effectiveness of a Rehabilitation Program for Orthopedic and Neurological Patients |
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