Table 2.
Summary of the characteristics of the18 included studies .
| No | Author(s)/citation | Title | Year | Aim | Method | Number of included articles |
|---|---|---|---|---|---|---|
| 1 | Akay et al 28 | Artificial Intelligence for Clinical Decision Support in Acute Ischemic Stroke: A Systematic Review | 2023 | Reviewed AI-based clinical decision support systems in the development stage, specifically regarding methodological robustness and constraints for clinical implementation. | Systematic review | 121 |
| 2 | Al-Namankany 29 | Influence of Artificial Intelligence-Driven Diagnostic Tools on Treatment Decision-Making in Early Childhood Caries: A Systematic Review of Accuracy and Clinical Outcomes | 2023 | Aimed to assess the performance and applicability of machine learning algorithms in early childhood caries (ECC) prediction and detection. A comprehensive search was conducted to identify studies utilizing machine learning algorithms to predict or detect ECC. | Systematic review | 6 |
| 3 | Ali et al 30 | Improving Diagnosis and Prognosis of Lung Cancer Using Vision Transformers: A Scoping Review | 2023 | Aimed to identify the recent developments in vision transformer-based AI methods for lung cancer imaging applications. | Scoping review | 34 |
| 4 | Amin et al 31 | Artificial Intelligence to Improve Antibiotic Prescribing: A Systematic Review | 2023 | Explored whether the use of AI can improve antibiotic prescribing for human patients. | Systematic review | 5 |
| 5 | Benzinger et al 32 | Should Artificial Intelligence be Used to Support Clinical Ethical Decision-Making? A Systematic Review of Reasons | 2023 | Aimed to provide a comprehensive overview of the reasons given in the academic literature for and against the use of artificial intelligence-based applications in clinical ethical decision making. | Systematic review | 44 |
| 6 | Cresswell et al 33 | Investigating the Use of Data-Driven Artificial Intelligence in Computerized Decision Support Systems for Health and Social Care: A Systematic Review | 2020 | The objective of this study was to evaluate the effectiveness of artificial intelligence-based computerized decision support systems in health and social care settings. | Systematic review | 5 |
| 7 | Dang et al 34 | Extent of Use of Artificial Intelligence and Machine Learning Protocols in Cancer Diagnosis: A Scoping Review | 2023 | Aimed to explore the extent of actual use of artificial intelligence/machine learning protocols for diagnosing cancer in prospective settings | Scoping review | 18 |
| 8 | Fernandes et al 35 | Clinical Decision Support Systems for Triage in the Emergency Department Using Intelligent Systems: A Review | 2020 | The objective of this paper was to evaluate the impact of intelligent clinical decision support systems for triage on the enhancement of quality of care in the emergency department and to identify the challenges encountered regarding implementation. | Scoping review | 62 |
| 9 | Higgins et al 36 | Artificial Intelligence (AI) and Machine Learning (Ml) Based Decision Support Systems in Mental Health: An Integrative Review | 2023 | Aimed to investigate the incorporation of artificial intelligence (AI) and machine learning (ML) based decision support systems in mental health care settings. | Scoping review | 4 |
| 10 | Khan et al 37 | Adoption and Utilization of Medical Decision Support Systems in the Diagnosis of Febrile Diseases: A Systematic Literature Review | 2023 | Aimed to review the development, adoption, and utilization of medical decision-support systems in diagnosing Febrile Diseases | Systematic review | 128 |
| 11 | Liao et al 38 | Recent Advancement in Integrating Artificial Intelligence and Information Technology With Real-World Data for Clinical Decision-Making in China: A Scoping Review | 2023 | Aimed to provide an overview of the current status of artificial intelligence-/information technology-based clinical decision support tools in China. | Scoping review | 37 |
| 12 | Michel et al 39 | Clinical Decision Support System in Emergency Telephone Triage: A Scoping Review of Technical Design, Implementation and Evaluation | 2024 | Aimed to identify literature gaps for the future development and evaluation of clinical decision-support systems for emergency telephone triage. | Scoping review | 19 |
| 13 | Moazemi et al 40 | Artificial Intelligence for Clinical Decision Support for Monitoring Patients in Cardiovascular ICUs: A Systematic Review | 2023 | Aimed to investigate studies and tools that address artificial intelligence/machine learning-based approaches towards clinical decision support (CDS) for monitoring cardiovascular patients in intensive care units (ICUs). | Systematic review | 21 |
| 14 | Nida et al 41 | Applications of Artificial Neural Networks in Healthcare Organizational Decision-Making: A Scoping Review. | 2019 | The aim was to provide a seminal review of the applications of artificial neural networks to healthcare organizational decision-making. | Scoping review | 80 |
| 15 | Rahimi et al 42 | Application of Artificial Intelligence in Shared Decision Making: Scoping Review. | 2022 | The paper aimed to identify and evaluate published studies that had tested or implemented artificial intelligence to facilitate shared decision-making. | Scoping review | 6 |
| 16 | Tiwari et al 43 | Artificial Intelligence's Use in the Diagnosis of Mouth Ulcers: A Systematic Review | 2023 | Aimed to identify the application of AI in the diagnosis of various forms of mouth ulcers | Systematic review | 23 |
| 17 | Tricco et al 44 | Implemented Machine Learning Tools to Inform Decision-Making for Patient Care in Hospital Settings: A Scoping Review | 2023 | The aim was to identify machine learning tools that were used in hospital settings and to examine how they were implemented to inform decision-making for patient care. | Scoping review | 20 |
| 18 | Uzun Ozashin et al 45 | The Systematic Review of Artificial Intelligence Applications in Breast Cancer Diagnosis | 2023 | Aimed to provide detailed insights into AI applications in breast cancer diagnosis, categorize key specializations of interest to the academic community, and identify research themes in each category through citation and thematic issue analysis. | Systematic review | 36 |