Papers in the review
| Author | Title | Journal | Citation index |
|---|---|---|---|
| Abbasgholizadeh Rahimi et al. (2021) | Application of Artificial Intelligence in Community-Based Primary Health Care: Systematic Scoping Review and Critical Appraisal | Journal of Medical Internet Research | 5 |
| Ahmed et al. (2020) | Artificial intelligence with multi-functional machine learning platform development for better healthcare and precision medicine | Journal of biological databases and curation | 171 |
| Bray et al. (2018) | Global cancer statistics | Cancer Journal for Clinicians | 17378 |
| Cutillo et al. (2020) | Machine intelligence in healthcare—perspectives on trustworthiness, explainability, usability, and transparency | Npj Digital Medicine | 71 |
| Elfiky, Pany, Parikh, and Obermeyer (2018) | Development and Application of a Machine Learning Approach to Assess Short-term Mortality Risk Among Patients With Cancer Starting Chemotherapy | JAMA Network Open | 78 |
| Faust et al. (2018) | Automated detection of atrial fibrillation using long short-term memory network with RR interval signals | Computers in Biology and Medicine | 171 |
| Jordan and Mitchell (2015) | Machine learning: Trends, perspectives, and prospects | Science | 2 |
| Kazantsev, Ponomareva, Kazantsev, Digilov, and Huang (2012) | Development of e-health network for in-home pregnancy surveillance based on artificial intelligence | International Conference on Biomedical and Health Informatics | |
| Khanna, Sattar, and Hansen (2013) | Artificial intelligence in health–the three big challenges | The Australasian medical journal | 315 |
| Kleczyk, Bana, and Arora (2021) | Leveraging Advanced Analytics to Understand the Impact of the COVID-19 Pandemic on Trends in Substance Use Disorders | Addictions - Diagnosis and Treatment | 0 |
| Ma and Tavares (2015) | A Novel Approach to Segment Skin Lesions in Dermoscopic Images Based on a Deformable Model | Journal of Biomedical and Health Informatics | 142 |
| Quinn, Jacobs, Senadeera, Le, and Coghlan (2022) | The three ghosts of medical AI: Can the black-box present deliver? | Artificial Intelligence in Medicine | 15 |
| Schirrmeister et al. (2017) | Deep learning with convolutional neural networks for EEG decoding and visualization | Deep Learning | 1367 |
| Sun (2021) | Adopting Artificial Intelligence in Public Healthcare: The Effect of Social Power and Learning Algorithms | International Journal of Environmental Research and Public Health | 0 |
| Tuli et al. (2020) | An ensemble deep learning based Smart Healthcare System for Automatic Diagnosis of Heart Diseases in integrated IoT and fog computing environments | Future Generation Computer Systems | 299 |
| Vamathevan et al. (2019) | Applications of machine learning in drug discovery and development | Nature reviews drug discovery | 463 |
| Ziuziański, Furmankiewicz, and Sołtysik-Piorunkiewicz (2014) | E-health artificial intelligence system implementation: case study of knowledge management dashboard of epidemiological data in Poland | International Journal of Biology and Biomedical Engineering | 8 |
| Dilsizian and Siegel (2014) | Artificial intelligence in medicine and cardiac imaging: harnessing big data and advanced computing to provide personalized medical diagnosis and treatment | Current cardiology reports | 16 |
| Bae, Lim, Kwon, and Nauck (2021) | Development of deep learning-based CT scoring system for COVID-19 pneumonia: Meta-analysis and validation study | PLoS ONE | 2 |
| Chen, Yu, Cheng and Hao (2019) | A Deep Learning Approach to Predict Clinical Outcomes from Electroencephalography in Critically Ill Patients | Anesthesiology | 8 |
| Davenport and Kalakota (2019) | Machine learning for healthcare: a review | Physiological Measurement | 265 |
| Garrido-Mesa, Adams, Gálvez, and Garrido-Mesa (2022) | Machine learning-based tools for healthcare personnel selection: systematic review | Journal of Medical Systems | 0 |
| Kivrak, Shah, and Chu (2021) | Comparison of deep learning techniques for COVID-19 detection using chest X-ray images | PeerJ Computer Science | 0 |
| Kumar et al. (2018) | Development of machine learning algorithms for prediction of impending fractures in patients with metastatic cancer to the spine | European Spine Journal | 30 |
| Li et al. (2021) | An intelligent edge computing system for data privacy protection in healthcare | IEEE Access | 2 |
| Müller (2016) | Automatic localization of anatomical landmarks in medical images using an anatomical atlas-based approach | Medical Image Analysis | 189 |
| Narain et al. (2021) | Artificial intelligence for predicting diabetic retinopathy progression: A systematic review | EClinicalMedicine | 0 |
| Zhang et al. (2021) | Deep Learning Predictive Analytics for Inpatient Glycemic Control | Journal of Diabetes Science and Technology | 0 |
| Author | Title | Journal | Citation index |
|---|---|---|---|
| Application of Artificial Intelligence in Community-Based Primary Health Care: Systematic Scoping Review and Critical Appraisal | 5 | ||
| Artificial intelligence with multi-functional machine learning platform development for better healthcare and precision medicine | 171 | ||
| Global cancer statistics | 17378 | ||
| Machine intelligence in healthcare—perspectives on trustworthiness, explainability, usability, and transparency | 71 | ||
| Development and Application of a Machine Learning Approach to Assess Short-term Mortality Risk Among Patients With Cancer Starting Chemotherapy | 78 | ||
| Automated detection of atrial fibrillation using long short-term memory network with RR interval signals | 171 | ||
| Machine learning: Trends, perspectives, and prospects | 2 | ||
| Development of e-health network for in-home pregnancy surveillance based on artificial intelligence | |||
| Artificial intelligence in health–the three big challenges | 315 | ||
| Leveraging Advanced Analytics to Understand the Impact of the COVID-19 Pandemic on Trends in Substance Use Disorders | 0 | ||
| A Novel Approach to Segment Skin Lesions in Dermoscopic Images Based on a Deformable Model | 142 | ||
| The three ghosts of medical AI: Can the black-box present deliver? | 15 | ||
| Deep learning with convolutional neural networks for EEG decoding and visualization | 1367 | ||
| Adopting Artificial Intelligence in Public Healthcare: The Effect of Social Power and Learning Algorithms | 0 | ||
| An ensemble deep learning based Smart Healthcare System for Automatic Diagnosis of Heart Diseases in integrated IoT and fog computing environments | 299 | ||
| Applications of machine learning in drug discovery and development | 463 | ||
| E-health artificial intelligence system implementation: case study of knowledge management dashboard of epidemiological data in Poland | 8 | ||
| Artificial intelligence in medicine and cardiac imaging: harnessing big data and advanced computing to provide personalized medical diagnosis and treatment | 16 | ||
| Development of deep learning-based CT scoring system for COVID-19 pneumonia: Meta-analysis and validation study | 2 | ||
| A Deep Learning Approach to Predict Clinical Outcomes from Electroencephalography in Critically Ill Patients | 8 | ||
| Machine learning for healthcare: a review | 265 | ||
| Machine learning-based tools for healthcare personnel selection: systematic review | 0 | ||
| Comparison of deep learning techniques for COVID-19 detection using chest X-ray images | 0 | ||
| Development of machine learning algorithms for prediction of impending fractures in patients with metastatic cancer to the spine | 30 | ||
| An intelligent edge computing system for data privacy protection in healthcare | 2 | ||
| Automatic localization of anatomical landmarks in medical images using an anatomical atlas-based approach | 189 | ||
| Artificial intelligence for predicting diabetic retinopathy progression: A systematic review | 0 | ||
| Deep Learning Predictive Analytics for Inpatient Glycemic Control | 0 |
Source(s): Authors’ elaboration
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