President Trump announced a new health care records system aimed at making it easier for Americans to share their medical information with providers, involving major tech companies and emphasizing privacy and opt-in participation, though concerns remain about data security and legal compliance.
Experts advocate for routine documentation of menstrual cycle data in healthcare systems, highlighting its potential to improve diagnosis and understanding of various health conditions, address health inequalities, and enhance women's health throughout their lives. Currently, this data is underused and not systematically collected, which limits its benefits for clinical care and research.
A breakthrough AI model developed by researchers from the University of California, San Francisco and Stanford University can predict the onset of Alzheimer's disease up to seven years in advance by analyzing over 5 million health records. The AI system combines analyses of various risk factors, such as high blood pressure, high cholesterol, vitamin D deficiency, and depression, to calculate the likelihood of developing Alzheimer's. It also identified osteoporosis as a significant risk factor for women and found connections between Alzheimer's, osteoporosis, and a gene variant, providing new opportunities for studying the disease's development. This approach could pave the way for early intervention and a better understanding of Alzheimer's and potentially other hard-to-diagnose diseases.