Artificial Intelligence and Machine Learning in Medical Devices

Virtual Conference
October 20, 2020

Artificial Intelligence and Machine Learning in Medical Devices

The Food and Drug Administration (FDA) is announcing a forthcoming public advisory committee meeting of the Patient Engagement Advisory Committee. The general function of the committee is to provide advice to the Commissioner, or designee, on complex issues relating to medical devices, the regulation of devices, and their use by patients. The meeting will be open to the public.

On October 22, 2020, the committee will discuss and make recommendations on the topic “Artificial Intelligence (AI) and Machine Learning (ML) in Medical Devices.” Specifically, we will discuss the composition of the datasets on which the software “learns”, components of the device information shared with patients, and factors that impact patient trust in the technology.

Large clinical datasets are used to train and improve AI/ML algorithms, allowing transformational improvements in the diagnosis, clinical decision making, and treatment of patients. Devices using AI/ML technology will transform healthcare delivery by increasing efficiency of key processes in the treatment of patients. Health products powered by AI/ML are streaming into our lives, from virtual doctor apps to wearable sensors and drugstore chatbots to algorithms for detecting cancer in mammography and interpretations of chest X rays.

Despite the rapid advancement and integration, AI/ML systems may have algorithmic biases, limited generalizability, and lack transparency in their assumptions based on potential limitations of training datasets. The recommendations provided by the committee will address the importance of including various demographic groups in AI/ML algorithm development. The recommendations will also address the impact of the user interface and transparency including what information and how the information about the devices could be communicated to foster patient trust in the AI/ML devices.