Scope of Artificial Intelligence (AI) in Data Privacy and Security Concerns in Healthcare: A Narrative Review

This study looks at how artificial intelligence (AI) affects patient data security and privacy in healthcare. AI, which can think like humans, is improving healthcare by making diagnostics better, personalizing treatments, and making hospital operations more efficient. However, there are big concerns about keeping patient data private and secure. AI needs a lot of data, which increases the risk of unauthorized access to sensitive information. This raises ethical issues and the potential misuse of personal data. Devices like wearables and the Internet of Medical Things (IoMT) make these problems worse. The study explores methods to protect privacy, such as special encryption techniques and secure data processing methods. It highlights the importance of strong authentication, maintaining data accuracy, and being transparent about how AI systems use data. Ethical concerns like bias and accountability are also discussed. The study concludes that while AI can greatly improve healthcare, it is crucial to have strong security measures to protect patient data. By doing this, healthcare systems can ensure patient privacy, build trust, and use AI responsibly and effectively, creating a safer and more reliable healthcare environment.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-03-28
DOI
https://doi.org/10.5281/zenodo.15101069
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Scope of Artificial Intelligence (AI) in Data Privacy and Security Concerns in Healthcare: A Narrative Review

Zenodo (CERN European Organization for Nuclear Research)
Artificial Intelligence in Healthcare and Education
article

Scope of Artificial Intelligence (AI) in Data Privacy and Security Concerns in Healthcare: A Narrative Review

article en

Abstract

This study looks at how artificial intelligence (AI) affects patient data security and privacy in healthcare. AI, which can think like humans, is improving healthcare by making diagnostics better, personalizing treatments, and making hospital operations more efficient. However, there are big concerns about keeping patient data private and secure. AI needs a lot of data, which increases the risk of unauthorized access to sensitive information. This raises ethical issues and the potential misuse of personal data. Devices like wearables and the Internet of Medical Things (IoMT) make these problems worse. The study explores methods to protect privacy, such as special encryption techniques and secure data processing methods. It highlights the importance of strong authentication, maintaining data accuracy, and being transparent about how AI systems use data. Ethical concerns like bias and accountability are also discussed. The study concludes that while AI can greatly improve healthcare, it is crucial to have strong security measures to protect patient data. By doing this, healthcare systems can ensure patient privacy, build trust, and use AI responsibly and effectively, creating a safer and more reliable healthcare environment.

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 57%
Artificial Intelligence in Healthcare and Education
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Scope of Artificial Intelligence (AI) in Data Privacy and Security Concerns in Healthcare: A Narrative Review · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS