Industry Perspectives

Inventory devices, map PHI flows, score clinical impact, and align IoT risk with FDA, HIPAA, and AAMI requirements.

Learn 7 AI evaluation methods for cybersecurity detection and triage, including rubrics, benchmarks, golden sets, human review, and LLM judge workflows.

How FDA Section 524B forces SBOMs, postmarket plans, secure design, and access controls for medical IoT — a patient-safety approach.

Role-based PHI access, least-privilege rules, break-glass limits, MFA, session timeouts, HR-tied account changes and audited log reviews.

Run safe, workflow-focused DAST: sanitized staging, logged-in FHIR tests, CI/CD gates, and prioritized triage.

Hospital AI documentation checklist: inventory, standard logs, data & model lineage, human overrides, tamper-proof storage, and framework mapping.

Checklist to meet FDA premarket cybersecurity: confirm scope, map data flows, prepare SBOM, document controls, and validate via testing.

Analysis of 10 failure points in medical device supply chains and immediate actions to reduce shortages, cyber and quality risks.

South Korea’s Financial Security Institute unveils an AI reliability and safety evaluation framework for finance.

Law firm investigates Baylor Genetics data breach exposing patient and employee personal information.

Law firm investigates Lone Star Community Health Center breach exposing 250,130 patients' personal and medical data.

How DLP supports HIPAA: monitor, log, and control ePHI (email, endpoints, cloud) while pairing tools with risk analysis and governance.

Five IoT incident-response metrics—MTTD, MTTA/MTTR-start, containment, recovery, improvement—mapped to NIST CSF for safer device operations.

AI should triage and continuously update healthcare vendor risk, but final high‑impact decisions must remain human‑controlled.

EDR stops attacks fast in healthcare by isolating devices, blocking harmful behavior, and matching automation to patient-safety needs.

Practical guardrails for safe healthcare AI: validation, monitoring, bias testing, vendor controls, and HIPAA compliance.

Protect research data and IP when working with AI drug discovery vendors. Learn top threats, governance steps, technical defenses, and continuous monitoring.

ISO 27001 and GDPR together secure patient data, reduce compliance gaps, and align incident response with GDPR’s 72-hour breach rule.

NCQA, AAAHC, and TJC vendor credentialing, security, and 2025 updates — why continuous monitoring and automation protect PHI and accreditation.

Practical guidance for healthcare vendors to design SOC 2–aligned PHI training: role-based lessons, regular refreshers, documentation, and audit-ready automation.

Centralize vendor inventories, prioritize critical suppliers, tighten contracts, and test contingency and incident response plans to reduce supply chain failures.

How the NIST Cybersecurity Framework boosts healthcare security—faster detection, fewer breaches, lower cyber insurance costs, and stronger vendor risk oversight.

Monitor AI in healthcare: set interpretability goals, apply XAI (SHAP, LIME, Grad-CAM), stream EHR data to real-time dashboards, and audit for bias and compliance.

Steps healthcare organizations must take to vet AI/ML vendors for FDA clearance, HIPAA security, PCCPs, and ongoing performance monitoring.