Table 1 Previous review studies utilizing various methodologies in the clinical domain
Existing studies | Literature methodologies | The outcome of the analysis |
|---|---|---|
Brnabic and Hess (2021) [8] | 34 articles, systematic review | Found a wide assortment of approaches, methods, techniques, software and validation procedures utilized in using ML/DL strategies to illuminate patient-provider decision making |
Robles Mendo et al. (2021) [27] | 20 articles, (PRISMA framework, systematic review | Reviewed commercial applications found in the best-known commercial platforms |
Salazar-Reyna et al. (2020) [42] | 576 articles, systematic review | Assessed and synthesized the published literature related to applying data analytics, big data, data mining, and ML to healthcare engineering systems |
Verma et al. (2021) [47] | 15 articles, systematic review | Utilized ML/DL strategies at various phases of exploiting datasets consisting of patient-detailed outcome measures for anticipating clinical outcomes, introducing the promising study and demonstrating the utility of patient-reported outcome measures data for developmental research, and personalized treatment and precision medicine with the help of ML-based decision-support systems |