Privacy-Preserving Data Mining Methods Metrics and Applications in Healthcare Informatics

Their fields have a profound interest in PPDM as a technical progress in health informatics, balancing the need to extract valuable information for clinical decisions while preserving sensitive data. Classic federated learning (FL) models have various limitations like intensive computational loads a...

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Ngā taipitopito rārangi puna kōrero
Ngā kaituhi matua:	Shukla Abhay, Chaurasia Shubham, Pandey Gaurav, Kumar Shukla Sanjeev, Singh Parihar Subhash, P B Edwin Prabhakar
Hōputu:	Artigo
Reo:	Inglês
I whakaputaina:	EDP Sciences 2025-01-01
Rangatū:	ITM Web of Conferences
Ngā marau:	federated learning in healthcare privacy-preserving data mining frameworks differential privacy in medical datasets blockchain for patient healthcare records scalable deep learning applications in healthcare healthcare data proteomics
Urunga tuihono:	https://www.itm-conferences.org/articles/itmconf/pdf/2025/07/itmconf_icsice2025_04002.pdf
Ngā Tūtohu:	Tāpirihia he Tūtohu Kāore He Tūtohu, Me noho koe te mea tuatahi ki te tūtohu i tēnei pūkete!

Privacy-Preserving Data Mining Methods Metrics and Applications in Healthcare Informatics

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