Machine learning prediction of mild cognitive impairment and its progression to Alzheimer’s disease
Health Science Report 2023: Effective screening for mild cognitive impairment (MCI) as a risk factor for developing Alzheimer’s disease is a crucial step in helping aging population with their needs Early detection and automated screening for MCI and dementia could offer opportunities for deliberate study and recruitment into trials for developing other potentially useful therapeutics or interventions. The study results were published in October, 2023.
Targeting repetitive laboratory testing with electronic health records-embedded predictive decision support: A pre-implementation study
March, 2023: Dr. Jonathan Chen’s lab recently published “Targeting repetitive laboratory testing with electronic health records: a pre-implementation study” in Clinical Biochemistry with funding from the SAGE Pilot Award Program.
Exploratory studies of microbiome in healthy human aging
October, 2022: Dr. Xin Zhou’s recent work, “Exploratory studies of oral and fecal microbiome in healthy human aging”, was published in Frontiers in Aging. https://pubmed.ncbi.nlm.nih.gov/36338834/
Award for Inclusion Research
Dr. Juan Banda’s lab was recently awarded the 2022 Google Research Award for Inclusion Research for the project “Towards more equitable representation of Latin American Spanish natural language processing resources for social media mining of health-related applications”.
Pressing Problems and Emerging Solutions in Aging Research
April 15, 2022: A collaborative symposium with scholars from San Jose State University (SJSU), Center for Healthy Aging in Multicultural Populations (CHAMP) & Stanford Aging and Ethnogeriatrics (SAGE) Research Center highlighted current research and practice concerns in the field of aging.
Stanford Researchers Named to Clinical Research Forum Top Ten List
March 2022: Dr. James Zou, Lead of the SAGE Center Methods Core, has received the Clinical Research Forum 2022 Top Ten Clinical Research Achievement Award in recognition of his study, “Evaluating eligibility criteria of oncology trials using real-world data and AI,” the results of which were published in Nature last year.
The study focused on using data science and artificial intelligence (AI) to design clinical trials, with a specific focus on making clinical trials more inclusive. “Trials frequently have pages and pages of eligibility criteria, which filters out a significant number of patients who would otherwise gain access to the latest treatments,” explained Dr. Zou. “These restrictions can also lead to the exclusion of female, minority, and older patients.”