https://www.selleckchem.com/products/PIK-75-Hydrochloride.html The increasing volume of biomedical data in chemistry and life sciences requires development of new methods and approaches for their analysis. Artificial Intelligence and machine learning, especially neural networks, are increasingly used in the chemical industry, in particular with respect to Big Data. This editorial highlights the main results presented during the special session of the International Conference on Neural Networks organized by "Big Data in Chemistry" project and draws perspectives on the future progress of the field. Subjective cognitive decline (SCD) is recognized as a risk stage for Alzheimer's disease (AD) and other dementias, but its prevalence is not well known. We aimed to use uniform criteria to better estimate SCD prevalence across international cohorts. We combined individual participant data for 16 cohorts from 15 countries (members of the COSMIC consortium) and used qualitative and quantitative (Item Response Theory/IRT) harmonization techniques to estimate SCD prevalence. The sample comprised 39,387 cognitively unimpaired individuals above age 60. The prevalence of SCD across studies was around one quarter with both qualitative harmonization/QH (23.8%, 95%CI = 23.3-24.4%) and IRT (25.6%, 95%CI = 25.1-26.1%); however, prevalence estimates varied largely between studies (QH 6.1%, 95%CI = 5.1-7.0%, to 52.7%, 95%CI = 47.4-58.0%; IRT 7.8%, 95%CI = 6.8-8.9%, to 52.7%, 95%CI = 47.4-58.0%). Across studies, SCD prevalence was higher in men than women, in lower levels of education, in Asian and Black African people compared to White people, in lower- and middle-income countries compared to high-income countries, and in studies conducted in later decades. SCD is frequent in old age. Having a quarter of older individuals with SCD warrants further investigation of its significance, as a risk stage for AD and other dementias, and of ways to help individuals with SCD who seek medical advic