Industry Perspectives

Secure patient data, build explainable and resilient AI models, enforce governance, and monitor systems in real time to prevent harm and privacy breaches.

Secure FHIR APIs for compliant healthcare data exchange: authentication (OAuth/SMART), consent and identity, API gateways, and third-party risk management.

Explore the challenges and best practices for ensuring FERPA compliance when integrating AI into healthcare education.

Explains FDA's 2025 cybersecurity rules for medical devices, including mandatory SBOMs, lifecycle obligations, 30-day disclosures and stricter enforcement.

FDA's 2025 cybersecurity guidance treats incident response as a patient-safety requirement, mandating lifecycle risk management, SBOMs and 30‑day notices.

Measure healthcare de-identification across accuracy, privacy risk, and data utility; compare text and DICOM benchmarks to balance privacy and usability.

Ethical AI in healthcare needs enforceable governance: clear roles, measurable controls, and continuous oversight to prevent harm and ensure fairness.

Explore the critical role of encryption in transit for healthcare IT, ensuring compliance and safeguarding patient data.

Explore how emerging blockchain privacy standards are transforming digital health while navigating complex regulatory challenges and enhancing data security.

Emerging AI privacy rules in healthcare require disclosure, clinician oversight, and tighter data protections — complicating multi-state and international compliance.

Emergency departments face critical risks from vendor systems that can compromise patient care and safety. Learn how to mitigate these threats effectively.

Explore how dynamic data classification enhances HIPAA compliance by ensuring real-time protection and accurate management of sensitive healthcare data.

Balancing AI innovation and patient safety: ethical principles, cybersecurity, XAI, governance, and real-time risk management for healthcare organizations.

Analysis of DeepSeek open-source AI models' jailbreaking vulnerabilities and resulting cybersecurity, privacy, and geopolitical risks.

Learn how to classify healthcare data in the cloud for HIPAA compliance, ensuring patient data security and reducing risks effectively.

Cybersecurity is the leading threat to healthcare systems in 2025, driven by outdated technology and increasing cyberattacks, impacting patient care and finances.

FDA 510(k) cybersecurity testing: threat modeling, SBOMs, vulnerability scans, penetration tests, and eSTAR documentation for compliant submissions.

AI is reshaping cyber warfare in healthcare, accelerating phishing, ransomware, and supply‑chain attacks while targeting AI‑powered clinical tools. This article breaks down why attackers focus on healthcare, how AI enhances cyberattacks, and the essential defenses—Zero Trust, MFA, immutable backups, real‑time monitoring, and AI governance—that organizations must implement.

Healthcare cloud security: risks—misconfigurations, weak IAM, vendor/API breaches and ransomware—and defenses like MFA, CSPM, immutable backups, and SIEM.

Practical steps to assess cloud vendor security, enforce HIPAA/HITRUST, and ensure business continuity to protect patient data and care delivery.

Explore the differences between cloud and on-premise PHI audits, including compliance, control, costs, and best practices for managing audits.

Ensure compliance with HIPAA and HITECH by mastering PHI audit documentation in the cloud, protecting patient data and avoiding costly penalties.

Secure cloud backups in healthcare: prevent ransomware and breaches with AES-256, immutable storage, RBAC, multi-region copies, and regular recovery testing.

How AI improves diagnosis and workflows while managing data privacy, bias, and cybersecurity risks through governance, vendor evaluation, and human oversight.