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ABSTRACT Background Post-stroke cognitive impairment (PSCI) severely affects patients’ daily living and independence, with limited treatment options. Repetitive transcranial magnetic stimulation (rTMS) shows promise but inconsistencies in reported effect sizes across cognitive domains.
Abstract Cardiovascular disease (CVD) and depression frequently co-occur, yet systematic depression screening remains underutilized in routine cardiac care. This study aimed to develop and compare machine learning algorithms for identifying concurrent depressive symptoms in middle-aged and elderly CVD patients. Data from 2,204 participants aged ≥ 45 years with physician-diagnosed CVD were obtained from the 2018 China Health and Retirement Longitudinal Study.
1 Introduction High-throughput screening (HTS) serves as a pivotal tool for lead discovery. A canonical approach for hit identification involves utilizing automated instrumentation to conduct exhaustive individual compound screening, yet this method often relies on expensive equipment and reagents, rendering HTS costly.
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