The field of artificial intelligence (AI) is growing at an astonishing rate.
Between 2017 and 2018, global venture funding in AI-focused startups grew by an estimated 50%, surpassing the $19 billion mark. Although it’s easy to see the influence of AI within the IT sector, the reality is that AI is branching into and disrupting other industries, including healthcare and medical devices.
Artificial intelligence (AI) is the science and engineering of making intelligent machines, specifically intelligent computer programs using models based on a statistical analysis of data, expert systems that primarily rely on if-then statements, and machine learning.
Machine learning (ML) is an AI technique that can be used to design and train software algorithms to learn from and act on data, essentially creating adaptive algorithms that have the prospective to continuously enhance device performance in real-time. In healthcare, ML can be used to improve patient outcomes.
AI in medical devices is a significantly growing part of the healthcare industry with the potential to improve patient care, as well as increasing the efficiency of administrative practices by automating tasks and achieving faster results.
Risk Categorization for Medical Devices:
The FDA categorizes medical devices based on their risks and the regulatory controls necessary to provide a reasonable assurance of safety and efficiency. It combines the seriousness of the medical condition and the importance of the information provided by the AI/ML-based SaMD to the healthcare decision. The risk-based approach to categorize SaMD is based on the intended use. The four categories, ranging from lowest (I) to highest risk (IV), reflect the risk associated with the clinical situation and device use.
Artificial Intelligence/Machine Learning: Software as a Medical Device (SaMD):
The greatest benefits of AI/ML in software resides in its capability to learn from real-world use cases, and respond to an experience to improve its performance. By learning from real-world feedback (training) to using this feedback to improve its performance (adaptation), AI/ML make software as a medical device (SaMD) adaptable.
To learn more about the specifics, check out our blog Software as a Medical Device: Everything You Need to Know about SaMD, to see how SaMD typically powers technology and connectivity to devices in order to monitor safety, efficiency, and performance.
New Trends in AI for Medical Devices:
Current emerging applications for medical devices powered by AI/ML seem to be divided in a few categories, however, the possibilities for AI/ML related devices are numerous. These Include:
- Management of Chronic Diseases Healthcare providers use machine learning to manage chronic conditions of patients by examining data source and creating algorithms to proactively treat their patients.
- Detecting Cancer in Mammography Breast cancer screening via mammography is a broadly accepted tool for breast cancer screening and another area where AI can be applied. With current imaging and analysis tools, cancer cells are often covered by dense breast tissues, but with the use of artificial intelligence, the risk of errors in reading these complicated images will soon be reduced.
- Medical Imaging Companies are integrating AI-driven platforms in medical scanning devices to expand image clarity and clinical outcomes by finding patterns in data humans cannot see. Whether in image data or non-image data, AI can see things invisible to the human eye.
- In Vitro Diagnostic Tools AI can be applied to in vitro diagnostics using real-time imaging to capture fluorescence signals as cells pass through a microfluidic channel. An AI algorithm could be used to distinguish cells by size, shape, and emission wavelength, and can categorize the cells as predictors of certain diseases.
- Diagnosis of Degenerative Brain Diseases The use of an intelligent system that accumulates, manages, analyzes, and automatically identifies neurological abnormalities is crucial. The application of AI in this area will improve the consistency of diagnosis and increase the success of treatment.
The Future of AI for Medical Devices:
AI in medical devices will continue to advance and pave the way for more technological innovations in diagnostics, imaging, mobile computing, and wearables. By integrating AI, medical devices will become more consistent, accurate, and quick in delivering results.
With AI gaining more traction for practical use cases and the amount of published research on the its growing medical applications, it seems certain regulators and the medical community at large are realizing the positive impact of AI in medical device development.
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