Is Clinical Decision Support Safe?
Clinical Decision Support — Nerq Trust Score 47.2/100 (D grade). Score based on 5 independent trust signals.
Clinical Decision Support is a software tool with a Nerq Trust Score of 47.2/100 (D), based on 5 independent data dimensions. Security: 0/100. Maintenance: 1/100. Popularity: 0/100. Data sourced from multiple public sources including package registries, GitHub, NVD, OSV.dev, and OpenSSF Scorecard. Last updated: n/a. Machine-readable data (JSON).
Is Clinical Decision Support safe?
Trust Score Breakdown — Clinical Decision Support has a Nerq Trust Score of 47.2/100 (D). Measured across 5 independent trust signals.
What is Clinical Decision Support's trust score?
Clinical Decision Support has a Nerq Trust Score of 47.2/100, earning a D grade. This score is based on 5 independently measured dimensions including security, maintenance, and community adoption.
What are the key security findings for Clinical Decision Support?
Clinical Decision Support's strongest signal is compliance at 48/100. No known vulnerabilities have been detected.
What is Clinical Decision Support and who maintains it?
| Author | Durgaprasadpenumuru |
| Category | Health |
| Source | https://github.com/Durgaprasadpenumuru/Clinical-Decision-Support |
| Frameworks | langchain · crewai |
| Protocols | rest |
Regulatory Compliance
| EU AI Act Risk Class | MINIMAL |
| Compliance Score | 48/100 |
| Jurisdictions | Assessed across 52 jurisdictions |
Popular Alternatives in health
What Is Clinical Decision Support?
Clinical Decision Support is a software tool in the health category: AI-driven medical triage and physician briefing system.. Nerq Trust Score: 47/100 (D).
Nerq independently analyzes every software tool, app, and extension across multiple trust signals including security vulnerabilities, maintenance activity, license compliance, and community adoption.
How Nerq Assesses Clinical Decision Support's Safety
Nerq's Trust Score is calculated from 13+ independent signals aggregated into five dimensions. Here is how Clinical Decision Support performs in each:
- Security (0/100): Clinical Decision Support's security posture is poor. This score factors in known CVEs, dependency vulnerabilities, security policy presence, and code signing practices.
- Maintenance (1/100): Clinical Decision Support is potentially abandoned. We track commit frequency, release cadence, issue response times, and PR merge rates.
- Documentation (1/100): Documentation quality is insufficient. This includes README completeness, API documentation, usage examples, and contribution guidelines.
- Compliance (48/100): Clinical Decision Support is compliance gaps exist. Assessed against regulations in 52 jurisdictions including the EU AI Act, CCPA, and GDPR.
- Community (0/100): Community adoption is limited. Based on GitHub stars, forks, download counts, and ecosystem integrations.
The overall Trust Score of 47.2/100 (D) is the weighted combination of these measured signals. It is a measurement, not a pass/fail or suitability judgment — weigh the individual signals against your own requirements.
Who Typically Evaluates Clinical Decision Support?
Clinical Decision Support is commonly evaluated by:
- Developers and teams working with health tools
- Organizations evaluating AI tools for their stack
- Researchers exploring AI capabilities in this domain
How to read the signals: Clinical Decision Support's measured signals (security 0/100, maintenance 1/100, documentation 1/100, community 0/100) are shown above. These are measurements, not a suitability judgment — weigh each signal against the requirements of your own use case and risk tolerance.
How to Verify Clinical Decision Support's Safety Yourself
While Nerq provides automated trust analysis, we recommend these additional steps before adopting any software tool:
- Check the source code — Review the repository's security policy, open issues, and recent commits for signs of active maintenance.
- Scan dependencies — Use tools like
npm audit,pip-audit, orsnykto check for known vulnerabilities in Clinical Decision Support's dependency tree. - Review permissions — Understand what access Clinical Decision Support requires. Software tools should follow the principle of least privilege.
- Test in isolation — Run Clinical Decision Support in a sandboxed environment before granting access to production data or systems.
- Monitor continuously — Use Nerq's API to set up automated trust checks:
GET nerq.ai/v1/preflight?target=Clinical-Decision-Support - Review the license — Confirm that Clinical Decision Support's license is compatible with your intended use case. Pay attention to restrictions on commercial use, redistribution, and derivative works. Some AI tools use dual licensing or have separate terms for enterprise customers that differ from the open-source license.
- Check community signals — Look at the project's issue tracker, discussion forums, and social media presence. A healthy community actively reports bugs, contributes fixes, and discusses security concerns openly. Low community engagement may indicate limited peer review of the codebase.
Common Safety Concerns with Clinical Decision Support
When evaluating whether Clinical Decision Support is safe, consider these category-specific risks:
Understand how Clinical Decision Support processes, stores, and transmits your data. Review the tool's privacy policy and data retention practices, especially for sensitive or proprietary information.
Check Clinical Decision Support's dependency tree for known vulnerabilities. Tools with outdated or unmaintained dependencies pose a higher security risk.
Regularly check for updates to Clinical Decision Support. Security patches and bug fixes are only effective if you're running the latest version.
If Clinical Decision Support connects to external APIs or services, each integration point is a potential attack surface. Audit all third-party connections, verify that data shared with external services is minimized, and ensure that integration credentials are rotated regularly.
Verify that Clinical Decision Support's license is compatible with your intended use case. Some AI tools have restrictive licenses that limit commercial use, redistribution, or derivative works. Using Clinical Decision Support in violation of its license can expose your organization to legal liability.
Clinical Decision Support and the EU AI Act
Clinical Decision Support is classified as Minimal Risk under the EU AI Act. This is the lowest risk category, meaning it faces minimal regulatory requirements. However, transparency obligations still apply.
Nerq's compliance assessment covers 52 jurisdictions worldwide. For organizations deploying AI tools in regulated environments, understanding these classifications is essential for legal compliance.
Best Practices for Using Clinical Decision Support Safely
Whether you're an individual developer or an enterprise team, these practices will help you get the most from Clinical Decision Support while minimizing risk:
Periodically review how Clinical Decision Support is used in your workflow. Check for unexpected behavior, permissions drift, and compliance with your security policies.
Ensure Clinical Decision Support and all its dependencies are running the latest stable versions to benefit from security patches.
Grant Clinical Decision Support only the minimum permissions it needs to function. Avoid granting admin or root access.
Subscribe to Clinical Decision Support's security advisories and vulnerability disclosures. Use Nerq's API to get automated trust score updates.
Create and maintain a clear policy for how Clinical Decision Support is used within your organization, including data handling guidelines and acceptable use cases.
Situations That Warrant Independent Review of Clinical Decision Support
Nerq's signals are one input. In the following situations, evaluate Clinical Decision Support's measured signals against your own requirements before making a decision:
- Environments handling sensitive or regulated data (healthcare, finance, government)
- Mission-critical systems where downtime has significant business impact
- Deployments with strict regulatory requirements that must be independently validated
For each situation, compare Clinical Decision Support's measured trust score of 47.2/100 and its individual signals against your organization's own criteria. Nerq does not assert whether Clinical Decision Support is suitable for any particular use.
How Clinical Decision Support Compares to Industry Standards
Nerq indexes over 6 million software tools, apps, and packages across dozens of categories. Among health tools, the average Trust Score is 62/100. Clinical Decision Support's score of 47.2/100 is below the category average of 62/100.
This suggests that Clinical Decision Support trails behind many comparable health tools. Organizations with strict security requirements should evaluate whether higher-scoring alternatives better meet their needs.
Industry benchmarks matter because they contextualize a tool's safety profile. A score that looks moderate in isolation may actually represent strong performance within a challenging category — or vice versa. Nerq's category-relative analysis helps teams make informed decisions by showing not just absolute quality, but how a tool ranks against its direct peers.
Trust Score History
Nerq continuously monitors Clinical Decision Support and recalculates its Trust Score as new data becomes available. Our scoring engine ingests real-time signals from source repositories, vulnerability databases (NVD, OSV.dev), package registries, and community metrics. When a new CVE is published, a major release ships, or maintenance patterns change, Clinical Decision Support's score is updated within 24 hours.
Historical trust trends reveal whether a tool is improving, stable, or declining over time. A tool that consistently maintains or improves its score demonstrates ongoing commitment to security and quality. Conversely, a downward trend may signal reduced maintenance, growing technical debt, or unresolved vulnerabilities. To track Clinical Decision Support's score over time, use the Nerq API: GET nerq.ai/v1/preflight?target=Clinical-Decision-Support&include=history
Nerq retains trust score snapshots at regular intervals, enabling trend analysis across weeks and months. Enterprise users can access detailed historical reports showing how each dimension — security, maintenance, documentation, compliance, and community — has evolved independently, providing granular visibility into which aspects of Clinical Decision Support are strengthening or weakening over time.
Clinical Decision Support vs Alternatives
In the health category, Clinical Decision Support scores 47.2/100. There are higher-scoring alternatives available. For a detailed comparison, see:
- Clinical Decision Support vs MedicalGPT — Trust Score: 52.2/100
- Clinical Decision Support vs open-health — Trust Score: 52.2/100
- Clinical Decision Support vs Awesome-AI4Med — Trust Score: 50.2/100
Key Takeaways
- Clinical Decision Support has a measured Nerq Trust Score of 47.2/100 (D) — a composite of independent signals, not a suitability judgment.
- Among health tools, Clinical Decision Support scores below the category average of 62/100 (a positional measurement relative to peers).
- The individual signals — security, maintenance, documentation, compliance, community — are shown above. Weigh them against your own requirements.
- Query the current measured values via Nerq's Preflight API.
Frequently Asked Questions
Is Clinical Decision Support Safe?
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See Also
Disclaimer: Nerq trust scores are automated measurements based on publicly available signals. They are not endorsements, verdicts, or guarantees of suitability. Always evaluate the signals against your own requirements.