23 Dec Data Mining as A Service in Medical Devices
Data mining is the field of Computer Science that forms the basis for data analytics. As the term specifies, it is utilized for ‘mining’ or extracting the most significant data from ‘Big Data’ or massive data sets. It not only serves as an extraction tool but also assists manufacturers and researchers in deriving hypotheses or conclusions from the existing Big Data sets, which can be applied toward improving existing services. Even though Data Mining is extensively utilized in commercial domains such as e-commerce or finance, it is indeed also proving to be vital for improving services in the health care domain. When utilized for developing or enhancing medical services, manufacturers should make sure their mining tool is safe and qualified enough to be integrated with medical devices.1
When coupled with modern technologies such as Machine Learning and Cloud Computing, the target product or the mined data is truly high quality. In health care, Data Mining can be applied to provide the ‘Forecasting’ or predictions by analyzing massive patient data sets. Using the same tools, unidentified patterns can be unraveled which may also serve as an early patient diagnostic tool. In one of the research studies, scientists collected data on more than 600 urine samples and used data mining to classify patients based on specific target characteristics. Additionally, pharmaceutical companies may use data mining to trace the common characteristics of a newly developed vaccine to predict its behavior against a specific set of patients. In another study, researchers ran an analysis on datasets of patients diagnosed with cancer. Using mining, they recorded specific elements such as common lifestyle habits that may initially look harmless but, in long term, may have a high probability of causing cancer.2
Data Mining facilitates early prediction plus diagnosis and when used in a medical setting, it should be highly accurate. Data mining itself may be a software tool or integrated with a medical device, but it should be verified and validated to check if the software tool meets all the required FDA guidelines. Validation begins by documenting the module designs and the entire software architecture, which may be performed by studying and drafting the software requirements from the system to the basic unit level. Moreover, manufacturers should perform rigorous testing and code inspections, starting from the very unit-level code blocks to the system-level modules. Such activities are conducted to verify if the mining tool satisfies its intended use. Also, testing with code inspections identifies any existing potential hazards in the system. All documentation including software designs, code inspections, and testing is sent to the FDA for review. If the FDA observes that the software tool meets the required industrial guidelines and if the tool possesses essential levels of safety, quality, and efficiency, the FDA provides the approval to label and market the tool in the US.
To summarize, Data Mining is one of the modern key tools for extracting relevant and required information from huge data sets. This information can be further utilized for generating valid conclusions or hypotheses and thus, for improving the overall system. Moreover, Data Mining facilitates features such as decision-making and forecasting which contributes towards the overall quality of patient care and adds the vital element of computing intelligence in the medical and health services. Do you have a Data Mining application that needs FDA approval? Our regulatory and software experts at EMMA International can help your medical device get FDA compliant. Contact us at 248-987-4497 or email@example.com for additional information.
1FDA (August 2019). Data Mining. Retrieved on December 21st 2020 from https://www.fda.gov/science-research/data-mining.
2Kayla Matthews (May 2019). How Data Mining Is Changing Health Care. Retrieved on December 21st 2020 from https://healthcareinamerica.us/how-data-mining-is-changing-health-care-27c1e9b3b372