Artificial intelligence in medical diagnostics: A review from a South African context
Tài liệu tham khảo
Abdelsalam, 2021, A novel approach of diabetic retinopathy early detection based on multifractal geometry analysis for OCTA macular images using support vector machine, IEEE Access, 9, 22844, 10.1109/ACCESS.2021.3054743
Adegun, 2020, Deep learning-based system for automatic melanoma detection, IEEE Access, 8, 7160, 10.1109/ACCESS.2019.2962812
Adepoju, 2020, Prediction and classification into benign and malignant using the clinical testing features, Int. J. Innov. Technol. Explor. Eng., 9, 55, 10.35940/ijitee.J7411.0891020
Alami, 2020, Artificial intelligence in health care: laying the foundation for responsible, sustainable, and inclusive innovation in low- and middle-income countries, Glob. Health, 16, 1, 10.1186/s12992-020-00584-1
Ali, 2020, Efficient lung nodule classification using transferable texture convolutional neural network, IEEE Access, 8, 175859, 10.1109/ACCESS.2020.3026080
R. Ashraf, S. Afzal, A.U.R. Rehman, S. Gul, J. Baber, M. Bakhtyar, I. Mehmood, O.H. Song, and M. Maqsood. 2020. “Region-of-interest based transfer learning assisted framework for skin cancer detection.” 10.1109/ACCESS.2020.3014701.
Babu, 2019, The robust computer-aided diagnostic system for lung nodule diagnosis, Int. J. Recent Technol. Eng., 8, 5670
Chandra, 2020, Automatic detection of tuberculosis related abnormalities in chest x-ray images using hierarchical feature extraction scheme, Expert Syst. Appl., 158, 10.1016/j.eswa.2020.113514
Chen, 2020, Detection of tuberculosis by the analysis of exhaled breath particles with high-resolution mass spectrometry, Scientific
Chiu, 2020, Breast cancer–detection system using PCA, multilayer perceptron, transfer learning, and support vector machine, IEEE Access, 8, 204309, 10.1109/ACCESS.2020.3036912
Cossy-Gantner, 2018, Artificial intelligence (AI) and global health: how can AI contribute to health in resource-poor settings?, BMJ Glob. Health, 3, 1
Dinesh Jackson Samuel, 2018, Tuberculosis (TB) detection system using deep neural networks, Neural Comput. Appl., 31, 1533, 10.1007/s00521-018-3564-4
Dinesh Jackson Samuel, 2020, Cybernetic microbial detection system using transfer learning, Multimed. Tools Appl., 79, 5225, 10.1007/s11042-018-6356-z
Du, 2016, 13
2018
Haq, 2021, Detection of breast cancer through clinical data using supervised and unsupervised feature selection techniques, IEEE Access, 4, 1
Iqbal, 2021, Prostate cancer detection using deep learning and traditional techniques, 9, 27085
Kabongo, 2015, Analysis of licensed South African diagnostic imaging equipment, Pan Afr. Med. J., 22, 10.11604/pamj.2015.22.57.7016
Kaur, 2019, Classification of mammograms using various feature extraction methods and machine learning. Pdf, Int. J. Recent Technol. Eng., 8, 5401
Khan, 2019, Artificial neural networks for prediction of tuberculosis disease, Front. Microbiol., 10
Kore, 2020, Detection of lung cancer disease using machine learning, International Journal of Engineering and Advanced Technology, 9, 810, 10.35940/ijeat.C6128.069520
Kumar, 2019, Brain tumor MRI segmentation and classification using ensemble classifier, International Journal of Recent Technology and Engineering, 8, 244
Lalithamani, 2019, Detection of oral cancer using deep neural based adaptive fuzzy system in data mining techniques, no, 5, 397
Mahomed, 2015, Development and implementation of an integrated chronic disease model in South Africa: lessons in the management of change through improving the quality of clinical practice, Int. J. Integr. Care, 15, 1, 10.5334/ijic.1454
Munadi, 2020, Image enhancement for tuberculosis detection using deep learning, IEEE Access, 8, 217897, 10.1109/ACCESS.2020.3041867
2015, National health insurance for South Africa, J. Indiana State Med. Assoc., 40, 4
Neela, 2019, A breast cancer detection using image processing and machine learning techniques, Int. J. Recent Technol. Eng., 8, 5250
Patel, 2020, Harnessing feature extraction techniques alongside CNN for diabetic retinopathy detection, Int. J. Recent Technol. Eng., 9, 422
Prabhu, 2019, Diabetic retinopathy screening using machine learning for hierarchical classification, Int. J. Innov. Technol. Explor. Eng., 8, 1943, 10.35940/ijitee.J9277.0881019
Prasanna Kumari, 2019, Abnormality detection of TB using instance learned classifier on lung CT images, Int. J. Recent Technol. Eng., 8, 979
Renuka, 2020, Mil based lung CT-image classification using CNN, Health Technol., 10.1007/s12553-019-00300-z
Shabut, 2018, An intelligent mobile-enabled expert system for tuberculosis disease diagnosis in real-time, Expert Syst. Appl., 114, 65, 10.1016/j.eswa.2018.07.014
Sharma, 2019, Lung cancer detection using convolutional neural network, Int. J. Eng. Adv. Technol., 8, 3256, 10.35940/ijeat.F8836.088619
Shravani, 2020, Lung cancer detection using local energy-based shape histogram (LESH) feature extraction using adaboost machine learning techniques, Int. J. Innov. Technol. Explor. Eng., 9, 167, 10.35940/ijitee.B7671.019320
Shravya, 2019, Prediction of breast cancer using supervised machine learning techniques, Int. J. Innov. Technol. Explor. Eng., 8, 1106
Tavakoli, 2021, Automated microaneurysms detection in retinal images using radon transform and supervised learning: application to mass screening of diabetic retinopathy, IEEE Access, 9, 67302, 10.1109/ACCESS.2021.3074458
Tranfield, 2003, Towards a methodology for developing evidence-informed management knowledge by means of systematic review, Br. J. Manag., 14, 207, 10.1111/1467-8551.00375
Z. Wang, M.O. Li, H. Wang, H. Jiang, Y. Yao, H.A.O. Zhang, and J. Xin. 2019. “Breast cancer detection using extreme learning machine based on feature fusion with CNN deep features” 7.
Wasekar, 2021, Machine learning for diabetic retinopathy detection using image processing, Int. J. Recent Technol. Eng., 9, 209
J. Wood (2020, Feb 17). These are the 10 biggest global health threats of the decade. Retrieved from World Economic Forum: https://www.weforum.org/agenda/2020/02/who-healthcare-challenges-2020s-climate-conflict-epidemics/# :∼:text=Rising%20 global%20rates%20of%20diseases,limited%20resources%20of%20poorer%20families.
J. Zheng, D. Lin, Z. Gao, S. Wang, M. He and J. Fan. 2020. “Deep learning assisted efficient adaboost algorithm for breast cancer detection and early diagnosis,” 1–10. 10.1109/ACCESS.2020.2993536.
Ziegelmayer, 2022, Cost-effectiveness of artificial intelligence support in computed tomography-based lung cancer screening, Cancers, 14, 1729, 10.3390/cancers14071729