Optimizing early breast cancer (BC) detection requires effective risk assessment tools. This retrospective study from Brazil showcases the efficacy of machine learning in discerning complex patterns within routine blood tests, presenting a globally accessible and cost-effective approach for risk evaluation. We analyzed complete blood count (CBC) tests from 396,848 women aged 40-70, who underwent breast imaging or biopsies within six months after their CBC test.
View Article and Find Full Text PDFPLoS One
March 2024
Atherosclerotic Cardiovascular Disease (ASCVD) represents the leading cause of death worldwide, and individual screening should be based on behavioral, metabolic, and genetic profile derived from data collected in large population-based studies. Due to the polygenic nature of ASCVD, we aimed to assess the association of genomics with ASCVD risk and its impact on the occurrence of acute myocardial infarction, stroke, or peripheral artery thrombotic-ischemic events at population level. CardioVascular Genes (CV-GENES) is a nationwide, multicenter, 1:1 case-control study of 3,734 patients in Brazil.
View Article and Find Full Text PDFData-independent acquisition (DIA) allows comprehensive proteome coverage, while it also potentially works as a unified protocol to determine a multitude of proteins found in blood. Because of its high specificity, mass spectrometry may greatly reduce the interference observed in other assays to evaluate blood markers. Here, we combined DIA with volumetric absorptive microsampling (VAMS) and automated proteomics sample processing in a platform to assess clinical markers.
View Article and Find Full Text PDFBackground: The Complete Blood Count (CBC) is a commonly used low-cost test that measures white blood cells, red blood cells, and platelets in a person's blood. It is a useful tool to support medical decisions, as intrinsic variations of each analyte bring relevant insights regarding potential diseases. In this study, we aimed at developing machine learning models for COVID-19 diagnosis through CBCs, unlocking the predictive power of non-linear relationships between multiple blood analytes.
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