Table 1.
List of selected journal articles.
| Author | Year | Title | Publication Title |
|---|---|---|---|
| Evans et al. | 2018 | The Challenge of Regulating Clinical Decision Support Software After 21st Century Cures | American Journal of Law & Medicine |
| Adadi et al. | 2019 | Gastroenterology Meets Machine Learning: Status Quo and Quo Vadis | Advances in bioinformatics |
| Shin et al. | 2019 | Current Status and Future Direction of Digital Health in Korea | The Korean Journal of Physiology& Pharmacology |
| Ahirwar et al. | 2020 | Interpretable Machine Learning in Health Care: Survey and Discussions | International Journal of Innovative Research in Technology and Management |
| Coppola et al. | 2021 | Human, All Too Human? An All-Around Appraisal of The “Artificial Intelligence Revolution” in Medical Imaging | Frontiers in Psychology |
| Wickramasinghe et al. | 2021 | A Vision for Leveraging the Concept of Digital Twins to Support the Provision of Personalized Cancer Care | IEEE Internet Computing |
| Bhatt et al. | 2022 | Emerging Artificial Intelligence–Empowered mHealth: Scoping Review | JMIR mHealth and uHealth |
| Chun et al. | 2022 | Prediction of Conversion to Dementia Using Interpretable Machine Learning in Patients with Amnestic Mild Cognitive Impairment | Frontiers in Aging Neuroscience |
| Gerussi et al. | 2022 | Artificial Intelligence for Precision Medicine in Autoimmune Liver Disease | Frontiers in Immunology |
| Iqbal et al. | 2022 | The Use and Ethics of Digital Twins in Medicine | Journal of Law, Medicine & Ethics |
| Ishengoma et al. | 2022 | Artificial Intelligence in Digital Health: Issues and Dimensions of Ethical Concerns | Innovación y Software |
| Khanna et al. | 2022 | Economics of Artificial Intelligence in Healthcare: Diagnosis vs. Treatment | Healthcare |
| Kline et al. | 2022 | Multimodal Machine Learning in Precision Health: A Scoping Review | npj Digital Medicine |
| Laccourreye et al. | 2022 | Explainable Machine Learning for Longitudinal Multi-Omic Microbiome | Mathematics |
| Roy et al. | 2022 | Demystifying Supervised Learning in Healthcare 4.0: A New Reality of Transforming Diagnostic Medicine | Diagnostics |
| Shazly et al. | 2022 | Introduction to Machine Learning in Obstetrics and Gynecology | Obstetrics & Gynecology |
| Wellnhofer et al. | 2022 | Real-World and Regulatory Perspectives of Artificial Intelligence in Cardiovascular Imaging | Frontiers in Cardiovascular Medicine |
| Wesołowski et al. | 2022 | An Explainable Artificial Intelligence Approach for Predicting Cardiovascular Outcomes Using Electronic Health Records | PLOS digital health |
| Albahri et al. | 2023 | A Systematic Review of Trustworthy and Explainable Artificial Intelligence in Healthcare: Assessment of Quality, Bias Risk, and Data Fusion | Information Fusion |
| Baumgartner et al. | 2023 | Fair and Equitable AI in Biomedical Research and Healthcare: Social Science Perspectives | Artificial Intelligence in Medicine |
| Bharati et al. | 2023 | A Review on Explainable Artificial Intelligence for Healthcare: Why, How, and When? | IEEE Transactions on Artificial Intelligence |
| Hong et al. | 2023 | Overcoming the Challenges in the Development and Implementation of Artificial Intelligence in Radiology: A Comprehensive Review of Solutions Beyond Supervised Learning | Korean Journal of Radiology |
| King et al. | 2023 | What Works Where and How for Uptake and Impact of Artificial Intelligence in Pathology: Review of Theories for a Realist Evaluation | Journal of Medical Internet Research |
| Kuwaiti et al. | 2023 | A Review of the Role of Artificial Intelligence in Healthcare | Journal of Personalized Medicine |
| Narayan et al. | 2023 | A Strategic Research Framework for Defeating Diabetes in India: A 21st-Century Agenda | Journal of the Indian Institute of Science |
| Vorisek et al. | 2023 | Artificial Intelligence Bias in Health Care: Web-Based Survey | Journal of Medical Internet Research |
| Zafar et al. | 2023 | Reviewing Methods of Deep Learning for Intelligent Healthcare Systems in Genomics and Biomedicine | Biomedical Signal Processing and Control |