Table 2.
Summary of artificial intelligence interventions and how they are being used for decision-making in the included studies.
| Study | Setting | Decision-making problem | AIa for decision-making |
| Wang et al [42] | Primary care | Knowledge and choices about antihyperglycemic medications | The tool provides patients and health care providers with tailored knowledge and choices about antihyperglycemic medications through the integration of electronic health record data. Patients and physicians can review patients’ conditions more comprehensively and tailor consultations to the patient’s current condition. |
| Frize et al [41] | Secondary care | Neonatal intensive care decisions | The tool allows health care providers to predict outcomes in neonatal intensive care and counsel families on the pros and cons of deciding to initiate or withdraw treatment. The tool also promotes parental involvement in the decision-making process. |
| Twiggs et al [43] | Secondary care | The decision about total knee arthroplasty | The AI intervention presents end users (patients and surgeons) with interpretable information relating to the risk of no improvement after total knee arthroplasty. This helps them decide whether to proceed with total knee arthroplasty. |
| Jayakumar et al [44] | Secondary care | The decision about total knee replacement | AI system provides patients with a personalized outcome report, which is then discussed with the surgeon during decision-making discussions. |
| Kökciyan et al [38,39]b | Primary care | The decision about treatment plans and options for stroke survivors | This tool supports the decision-making point by providing an up-to-date view of the patients’ situation based on personalized metrics and provides explanations for its recommendations. |