journal article·2024-03-19Open access

Special Issue on eHealth Innovative Approaches and Applications

Stefano Silvestri, Francesco Gargiulo

Applied Sciences· Volume 14· Issue 6

Abstract

Innovative ICT technologies, approaches and applications are becoming increasingly pervasive in several domains, including in medicine and healthcare [...]
Only a short abstract or summary was supplied by the source.
Source: crossref · Quality: short

Research context

OpenAlex topics: Artificial Intelligence in Healthcare · Mobile Health and mHealth Applications · IoT and Edge/Fog Computing

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Institute for High Performance Computing and Networking, ICAR-CNR, Via Pietro Castellino 111, 80131 Naples, Italy

Funding

European Union - NextGenerationEU - National Recovery and Resilience Plan (Piano Nazionale di Ripresa e Resilienza, PNRR) - Project: “SoBigData.it - Strengthening the Italian RI for Social Mining and Big Data Analytics” · European Commission

References (40)

Show source-provided references
1. Computational pathology: A survey review and the way forward10.1016/j.jpi.2023.100357 ↗
2. A systematic review of healthcare recommender systems: Open issues, challenges, and techniques10.1016/j.eswa.2022.118823 ↗
3. Wen, M.H., Bai, D., Lin, S., Chu, C.J., and Hsu, Y.L. (2022). Implementation and experience of an innovative smart patient care system: A cross-sectional study. BMC Health Serv. Res., 22.10.1186/s12913-022-07511-7 ↗
4. An intelligent environment for preventing medication errors in home treatment10.1016/j.eswa.2021.116434 ↗
5. Ajagbe, S.A., Awotunde, J.B., Adesina, A.O., Achimugu, P., and Kumar, T.A. (2022). Intelligent Healthcare: Infrastructure, Algorithms and Management, Springer Nature.
6. BioBERT: A pre-trained biomedical language representation model for biomedical text mining10.1093/bioinformatics/btz682 ↗
7. BERTMeSH: Deep contextual representation learning for large-scale high-performance MeSH indexing with full text10.1093/bioinformatics/btaa837 ↗
8. Singhal, K., Tu, T., Gottweis, J., Sayres, R., Wulczyn, E., Hou, L., Clark, K., Pfohl, S., Cole-Lewis, H., and Neal, D. (2023). Towards Expert-Level Medical Question Answering with Large Language Models. arXiv.
9. ChatDoctor: A Medical Chat Model Fine-Tuned on a Large Language Model Meta-AI (LLaMA) Using Medical Domain Knowledge
10. MED-Prompt: A novel prompt engineering framework for medicine prediction on free-text clinical notes
11. Ciampi, M., Sicuranza, M., and Silvestri, S. (2022). A Privacy-Preserving and Standard-Based Architecture for Secondary Use of Clinical Data. Information, 13.10.3390/info13020087 ↗
12. Empowering Healthcare With IoMT: Evolution, Machine Learning Integration, Security, and Interoperability Challenges10.1109/ACCESS.2024.3362239 ↗
13. Thapa, C., and Camtepe, S. (2021). Precision health data: Requirements, challenges and existing techniques for data security and privacy. Comput. Biol. Med., 129.10.1016/j.compbiomed.2020.104130 ↗
14. Chatterjee, P., Das Sharma, K., and Chakrabarti, A. (2024). Weakly supervised learning in domain transfer scenario for brain lesion segmentation in MRI. Multimed. Tools Appl., 1–17.10.1007/s11042-023-17888-0 ↗
15. Interactive medical image annotation using improved Attention U-net with compound geodesic distance10.1016/j.eswa.2023.121282 ↗
16. Silvestri, S., Gargiulo, F., and Ciampi, M. (2022). Iterative Annotation of Biomedical NER Corpora with Deep Neural Networks and Knowledge Bases. Appl. Sci., 12.10.3390/app12125775 ↗
17. Islam, S., Papastergiou, S., Kalogeraki, E.M., and Kioskli, K. (2022). Cyberattack Path Generation and Prioritisation for Securing Healthcare Systems. Appl. Sci., 12.10.3390/app12094443 ↗
18. Cyber threat assessment and management for securing healthcare ecosystems using natural language processing10.1007/s10207-023-00769-w ↗
19. Big Data for Healthcare Industry 4.0: Applications, challenges and future perspectives10.1016/j.eswa.2022.116912 ↗
20. Artificial intelligence in oncology: Current applications and future perspectives10.1038/s41416-021-01633-1 ↗
21. Busnatu, S., Niculescu, A.G., Bolocan, A., Petrescu, G.E.D., Păduraru, D.N., Năstasă, I., Lupușoru, M., Geantă, M., Andronic, O., and Grumezescu, A.M. (2022). Clinical Applications of Artificial Intelligence—An Updated Overview. J. Clin. Med., 11.10.3390/jcm11082265 ↗
22. Clinical information extraction applications: A literature review10.1016/j.jbi.2017.11.011 ↗
23. Gargiulo, F., Silvestri, S., and Ciampi, M. (2017, January 3–6). A Big Data architecture for knowledge discovery in PubMed articles. Proceedings of the 2017 IEEE Symposium on Computers and Communications (ISCC), Heraklion, Greece.10.1109/ISCC.2017.8024509 ↗
24. Investigation of physicians’ awareness and use of mHealth apps: A mixed method study10.1016/j.hlpt.2017.07.007 ↗
25. How physicians can empower patients with digital tools: A joint study of the Italian Scientific Society of Internal Medicine (FADOI) and the European Federation of Internal Medicine (EFIM)10.1007/s10389-020-01370-4 ↗
26. Liu, J., Chang, W., Wu, Y., and Yang, Y. (2017). Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval, ACM.
27. Hagen, M., Verberne, S., Macdonald, C., Seifert, C., Balog, K., Norvaag, K., and Setty, V. (2022). Advances in Information Retrieval, Springer International Publishing.10.1007/978-3-030-99739-7 ↗
28. Information centric network: Research challenges and opportunities10.1016/j.jnca.2015.02.001 ↗
29. Cybersecurity Challenges for PACS and Medical Imaging10.1016/j.acra.2020.03.026 ↗
30. Burstein, J., Doran, C., and Solorio, T. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding. Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers).
31. Wang, L., Yang, N., Huang, X., Jiao, B., Yang, L., Jiang, D., Majumder, R., and Wei, F. (2022). Text embeddings by weakly-supervised contrastive pre-training. arXiv.
32. Suvirat, K., Chairat, S., Horsiritham, K., Kongkamol, C., and Chaichulee, S. (2023, January 5–18). De-identification of Thai Free-text Clinical Notes. Proceedings of the 2023 15th Biomedical Engineering International Conference (BMEiCON), Pittsburgh, PA, USA.10.1109/BMEiCON60347.2023.10321968 ↗
33. Cheimonidis, P., and Rantos, K. (2023). Dynamic Risk Assessment in Cybersecurity: A Systematic Literature Review. Futur. Internet, 15.10.3390/fi15100324 ↗
34. Knezovic, J., Kovac, M., and Mlinaric, H. (2006, January 16–19). Classification and blending prediction for lossless image compression. Proceedings of the MELECON 2006–2006 IEEE Mediterranean Electrotechnical Conference, Malaga, Spain.10.1109/ITICT.2006.358233 ↗
35. Jodogne, S., Bernard, C., Devillers, M., Lenaerts, E., and Coucke, P. (2013, January 7–11). Orthanc—A lightweight, restful DICOM server for healthcare and medical research. Proceedings of the 2013 IEEE 10th International Symposium on Biomedical Imaging, San Francisco, CA, USA.10.1109/ISBI.2013.6556444 ↗
36. Cybersecurity in the Internet of Medical Things10.1016/j.hlpt.2021.100549 ↗
37. Hatzivasilis, G., Soultatos, O., Ioannidis, S., Verikoukis, C., Demetriou, G., and Tsatsoulis, C. (2019, January 29–31). Review of Security and Privacy for the Internet of Medical Things (IoMT). Proceedings of the 2019 15th International Conference on Distributed Computing in Sensor Systems (DCOSS), Santorini Island, Greece.10.1109/DCOSS.2019.00091 ↗
38. Bayrak, E.A., and Kirci, P. (2022). System Analysis & Intelligent Computing: Theory and Applications, Springer International Publishing.
39. Evaluation of vermillion border descriptors and relevance vector machines discrimination model for making probabilistic predictions of solar cheilosis on digital lip photographs10.1016/j.compbiomed.2015.04.024 ↗
40. Rees, D. (2024, March 08). Cyber Attacks in Healthcare: The Position across Europe. Available online: https://www.pinsentmasons.com/out-law/analysis/cyber-attacks-healthcare-europe.