Show source-provided references
3. Shah, F.D., Li, J.P., Shah, Y., and Shah, F. (2017, January 11–13). Broad Big Data Domain via Medical Big Data. Proceedings of the 4th International Conference on Systems and Informatics (ICSAI), Hangzhou, China.
10.1109/ICSAI.2017.8248383 ↗4. Personalized mid-course FDG-PET based adaptive treatment planning for non-small cell lung cancer using machine learning and optimization
10.1088/1361-6560/ac88b3 ↗5. Trends in Clostridioides difficile infection across a public health hospital system in New York City 2019–2021: A cautionary note
10.1016/j.ajic.2022.04.015 ↗6. Awan, M.J., Bilal, M.H., Yasin, A., Nobanee, H., Khan, N.S., and Zain, A.M. (2021). Detection of COVID-19 in Chest X-ray Images: A Big Data Enabled Deep Learning Approach. Int. J. Environ. Res. Public Health, 18.
10.3390/ijerph181910147 ↗7. Improving liver lesions classification on CT/MRI images based on Hounsfield Units attenuation and deep learning
10.1016/j.gep.2022.119289 ↗8. MRI data quality assessment for the RIN-Neuroimaging Network using the ACR phantoms
9. Safety and efficacy of lumen-apposing metal stents and double-pigtail plastic stents for endoscopic ultrasound-guided drainage of walled-off necrosis; a systematic review and meta-analysis
10.1080/07853890.2022.2164048 ↗10. Wang, J.P., and Li, X.H. (2023). Secure Medical Data Collection in the Internet of Medical Things Based on Local Differential Privacy. Electronics, 12.
10.3390/electronics12020307 ↗11. Establishment of a Chinese critical care database from electronic healthcare records in a tertiary care medical center
10.1038/s41597-023-01952-3 ↗12. Psarra, E., Apostolou, D., Verginadis, Y., Patiniotakis, I., and Mentzas, G. (2022). Context-Based, Predictive Access Control to Electronic Health Records. Electronics, 11.
10.3390/electronics11193040 ↗13. The Status Epilepticus in Adults: Results from a Tertiary Care Teaching Hospital in Karachi, Pakistan
10.3329/bjms.v22i1.61861 ↗16. Bhachawat, S., Shriram, E., Srinivasan, K., and Hu, Y.C. (2023). Leveraging Computational Intelligence Techniques for Diagnosing Degenerative Nerve Diseases: A Comprehensive Review, Open Challenges, and Future Research Directions. Diagnostics, 13.
10.3390/diagnostics13020288 ↗17. Discovering Long COVID Symptom Patterns: Association Rule Mining and Sentiment Analysis in Social Media Tweets
10.2196/37984 ↗19. De Fazio, R., Di Giovannantonio, R., Bellini, E., and Marrone, S. (2023). Explainabilty Comparison between Random Forests and Neural Networks-Case Study of Amino Acid Volume Prediction. Information, 14.
10.3390/info14010021 ↗22. Weakly Supervised Learning for Poorly Differentiated Adenocarcinoma Classification in GastricEndoscopic Submucosal Dissection Whole Slide Images
10.1177/15330338221142674 ↗24. Reinforcement learning with dynamic completion for answering multi-hop questions over incomplete knowledge graph
10.1016/j.ipm.2023.103283 ↗25. Mapping of the wind erodible fraction of soil by bidirectional gated recurrent unit (BiGRU) and bidirectional recurrent neural network (BiRNN) deep learning models
10.1016/j.catena.2023.106953 ↗26. Prediction of OCT images of short-term response to anti-VEGF treatment for diabetic macular edema using different generative adversarial networks
10.1016/j.pdpdt.2023.103272 ↗28. Yang, B., Zhu, X., Wei, B., Liu, M.Z., Li, Y.F., Lv, Z.H., and Wang, F.M. (2023). Computer Vision and Machine Learning Methods for Heat Transfer and Fluid Flow in Complex Structural Microchannels: A Review. Energies, 16.
10.3390/en16031500 ↗30. Benucci, M., Damiani, A., Russo, E., Guiducci, S., Li Gobbi, F., Fusi, P., Grossi, V., Amedei, A., Manfredi, M., and Infantino, M. (2022). The Association of uPA, uPAR, and suPAR System with Inflammation and Joint Damage in Rheumatoid Arthritis: suPAR as a Biomarker in the Light of a Personalized Medicine Perspective. J. Pers. Med., 12.
10.3390/jpm12121984 ↗33. da Costa, T.P., Gillespie, J., Pelc, K., Shenker, N., Weaver, G., Ramanathan, R., and Murphy, F. (2023). An Organisational-Life Cycle Assessment Approach for Internet of Things Technologies Implementation in a Human Milk Bank. Sustainability, 15.
10.3390/su15021137 ↗34. Lieberman, B., Kong, J.D., Gusinow, R., Asgary, A., Bragazzi, N.L., Choma, J., Dahbi, S.E., Hayashi, K., Kar, D., and Kawonga, M. (2023). Big data- and artificial intelligence-based hot-spot analysis of COVID-19: Gauteng, South Africa, as a case study. BMC Med. Inform. Decis. Mak., 23.
10.1186/s12911-023-02098-3 ↗35. Chen, F.Y., Gao, C.C., Gu, X., and Yue, T. (2023). Research on the Spatial and Temporal Differences in Public Response to Release-Type Communication to Stop Food Waste. Appl. Sci., 13.
10.3390/app13020736 ↗37. Elvas, L.B., Serrao, C., and Ferreira, J.C. (2023). Sharing Health Information Using a Blockchain. HealthCare, 11.
10.3390/healthcare11020170 ↗38. Emerging Technologies Used in Health Management and Efficiency Improvement during Different Contact Tracing Phases against COVID-19 Pandemic
10.1109/RBME.2022.3219433 ↗39. Addressing the Barriers to Clinical Trials Accrual in Community Cancer Centres Using a National Clinical Trials Navigator: A Cross-Sectional Analysis
10.1177/10732748221130164 ↗40. Ramirez-Arias, F.J., Garcia-Guerrero, E.E., Tlelo-Cuautle, E., Colores-Vargas, J.M., Garcia-Canseco, E., Lopez-Bonilla, O.R., Galindo-Aldana, G.M., and Inzunza-Gonzalez, E. (2022). Evaluation of Machine Learning Algorithms for Classification of EEG Signals. Technologies, 10.
10.3390/technologies10040079 ↗