Alzheimer’s disease is a healthcare albatross lurking in the background to prey upon our aging population. Despite considerable attention to detection and management of Alzheimer’s disease (AD), significant gaps remain.
While many traditional memory assessment tools are available, deficiencies in screening and detection accuracy and reliability remain prevalent. New research suggests use of technology in the form of artificial intelligence (AI) may present a solution for testing and managing the complex human health condition.
Worldwide, about 44 million people are living with AD or a related form of dementia. Although 82 percent of seniors in the United States say it’s important to have their thinking or memory checked, only 16 percent say they receive regular cognitive assessments.
And even with the development of new, simple online tests, numerous integrated and complex factors complicate the interpretation of memory evaluation test results. This presents a real challenge for clinicians and is a collective barrier for addressing the growing and widespread prevalence of AD.
As such, a team of researchers at Florida Atlantic University’s College of Engineering and Computer Science, SIVOTEC Analytics, HAPPYneuron, MemTrax, and Stanford University School of Medicine, believe AI can significantly help address these complex issues.
One challenge is determining the reliability and validity of new assessment instruments such as MemTrax — a very simple online memory test using image recognition. MemTrax is a supervised machine learning and predictive modeling tool that can serve as a clinical decision support screening tool for assessing cognitive impairment.
As published in the Journal of Alzheimer’s Disease, researchers determined MemTrax is an effective tool that can be administered as part of the online Continuous Recognition Tasks (M-CRT) test, in screening for variations in cognitive brain health.
Notably, a comparison of MemTrax to the recognized and widely utilized Montreal Cognitive Assessment Estimation of mild cognitive impairment underscores the power and potential of this new online tool. MemTrax improves the ability to evaluate short-term memory and aids in diagnostic support for cognitive screening and assessment for a variety of clinical conditions and impairments including dementia.
“Machine learning has an inherent capacity to reveal meaningful patterns and insights from a large, complex inter-dependent array of clinical determinants and the ability to continue to ‘learn’ from ongoing utility of practical predictive models,” said Taghi Khoshgoftaar, PhD, co-author and Motorola Professor in FAU’s Department of Computer and Electrical Engineering and Computer Science.
“Seamless use and real-time interpretation will enhance case management and patient care through innovative technology and practical and readily usable integrated clinical applications that could be developed into a hand-held device and app.”
For the study, the researchers used an existing dataset, which includes data from more than 18,000 individuals. They examined answers to general health screening questions (addressing memory, sleep quality, medications, and medical conditions affecting thinking) and demographic information. They also reviewed the test results from adults who took the MemTrax (M-CRT) test for episodic-memory screening.
“Findings from our study provide an important step in advancing the approach for clinically managing a very complex condition like Alzheimer’s disease,” said Michael F. Bergeron, PhD, senior author.
“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 health care providers to detect and anticipate further progression in this disease and myriad other aspects of cognitive impairment.”
AD is the sixth leading cause of death in the United States, affecting 5.8 million Americans. According to the Alzheimer’s Association, this number is projected to rise to 14 million by 2050. In 2019, AD and other dementias will cost the nation $290 billion. By 2050, these costs could rise as high as $1.1 trillion.
“With its widespread prevalence and escalating incidence and public health burden, it is imperative to ensure that the tools clinicians use for testing and managing Alzheimer’s disease and other related cognitive conditions are optimal,” said Stella Batalama, PhD, dean of FAU’s College of Engineering and Computer Science.
“Results from this important study provide new insights and discovery that has set the stage for future impactful and significant research.”
Photo: A team of researchers at Florida Atlantic University’s College of Engineering and Computer Science, SIVOTEC Analytics, HAPPYneuron, MemTrax, and Stanford University School of Medicine introduce supervised machine learning as a modern approach and new value-added complementary tool in cognitive brain health assessment and related patient care and management. Credit: Florida Atlantic University.