Artificial Intelligence Could Be 'Game Changer' in Detecting, Managing Alzheimer's Disease

A study published in the Journal of Alzheimer's Disease detailed supervised machine learning as a modern approach and complementary tool in cognitive brain health evaluation and management of people with Alzheimer's, reports Medical Xpress . "Machine learning has an inherent capacity to reveal meaningful patterns and insights from a large, complex interdependent array of clinical determinants and the ability to continue to 'learn' from ongoing utility of practical predictive models," said Florida Atlantic University Professor Taghi Khoshgoftaar. "Seamless use and real-time interpretation will enhance case management and . . . care through innovative technology and practical and readily usable integrated clinical applications that could be developed into a hand-held device and app." The researchers used an existing dataset to review answers to general health screening questions, demographic information, and test results from a sample of adults who took the MemTrax test for episodic-memory screening. "By analyzing a wide array of attributes across multiple domains of the human system, and functional behaviors of brain health, informed and strategically directed advanced data mining, supervised machine learning, and robust analytics can be integral, and in fact necessary, for healthcare providers to detect and anticipate further progression in this disease and myriad other aspects of cognitive impairment," noted SIVOTEC Analytics' Michael F. Bergeron.