Introduction

Artificial intelligence (AI) has become a transformative force in the medical field, powering diagnostic tools, predictive analytics, personalized treatment, and drug discovery. As these technologies evolve, so does the debate over their protection under intellectual property law. The central question is whether medical AI software should be treated merely as software (often excluded from patent protection in many jurisdictions) or as a genuine invention with patentable subject matter.

This article explores the patentability of medical AI software, analyzing international approaches, challenges in classification, and implications for innovation and public health.

Patentability of Software: A General Overview

Traditionally, patent law has been reluctant to grant protection to software. In many jurisdictions, software “as such” is excluded from patentability. The rationale is that software represents an abstract set of instructions rather than a technical solution.

• United States: The U.S. allows patents for software-related inventions if they meet the requirements of novelty, non-obviousness, and utility, and if they demonstrate a “technical effect.” However, the Supreme Court’s Alice v. CLS Bank (2014) decision limited patents on abstract ideas implemented on a computer.
• European Union: The European Patent Office (EPO) excludes “programs for computers as such” but permits patents where software produces a “further technical effect,” such as improved image processing in medical diagnostics.
• Other Jurisdictions: Countries like Japan, China, and South Korea have adopted flexible approaches, allowing software patents in fields where algorithms provide concrete technical contributions.

Medical AI: Beyond Traditional Software?

Medical AI applications often go beyond abstract data processing. Examples include:

• AI algorithms that analyze radiological images to detect early-stage cancers.
• Predictive models for patient deterioration in intensive care units.
• AI-driven robotic surgery systems with autonomous decision-making capabilities.

These applications arguably transcend the definition of mere software, offering a technical solution to a medical problem. The question, then, is whether such solutions should be classified as software tools (excluded from patents) or as inventions in medicine and technology (potentially patentable).

Challenges in Patent Protection for Medical AI

1. Algorithm Transparency and Disclosure

Patent law requires disclosure of the invention. Yet many AI systems, especially deep learning models, operate as “black boxes.” Explaining their functioning in a manner sufficient for patent law poses difficulties.

2. Novelty and Non-Obviousness

Medical AI often relies on training with pre-existing medical data. Determining what is “novel” versus what constitutes a predictable algorithmic adjustment can be complex.

3. Ethical and Public Health Concerns

Granting exclusive patent rights over critical medical AI tools may restrict access to life-saving technologies, raising ethical and policy questions. Some argue for alternative protections, such as trade secrets or data exclusivity, to balance innovation incentives with public interest.

4. Overlap with Other IP Regimes

• Copyright: Protects the source code of the AI software.
• Trade Secrets: Protect proprietary training data and algorithms.
• Patents: Should, in principle, protect only when there is a demonstrable technical effect that contributes to medical practice.

Policy Perspectives and Future Directions

• Hybrid Approaches: Some propose distinguishing between algorithmic code (copyright-protected) and technical medical applications (patent-protected).
• Public-Private Balance: Policymakers must weigh patent protection as an incentive for R&D against risks of monopolization in healthcare.
• AI-Specific Patent Frameworks: There is growing debate over creating specialized rules for AI-driven inventions, acknowledging their unique nature.

Conclusion

The question of whether medical AI software constitutes mere software or a patentable invention remains unsettled. While many medical AI applications demonstrate clear technical effects and innovative contributions, legal uncertainty persists due to the abstract nature of algorithms and varying international standards.

A balanced approach is needed: one that recognizes the inventive technical contributions of medical AI while ensuring equitable access to critical healthcare technologies. Ultimately, the future of medical AI patents may require a rethinking of traditional categories, bridging the gap between software and invention.