The Role of Machine Learning in the Detection of Cardiac Fibrosis in Electrocardiograms: Scoping Review.

Background: Cardiovascular disease remains the leading cause of mortality worldwide. Cardiac fibrosis impacts the underlying pathophysiology of many cardiovascular diseases by altering structural integrity and impairing electrical conduction. Identifying cardiac fibrosis is essential for the prognosis and management of cardiovascular disease; however, current diagnostic methods face challenges due to invasiveness, cost, and inaccessibility.

The practice of genomic medicine: A delineation of the process and its governing principles.

Genomic medicine, an emerging medical discipline, applies the principles of evolution, developmental biology, functional genomics, and structural genomics within clinical care. Enabling widespread adoption and integration of genomic medicine into clinical practice is key to achieving precision medicine. We delineate a biological framework defining diagnostic utility of genomic testing and map the process of genomic medicine to inform integration into clinical practice.

The Clinical Variant Analysis Tool: Analyzing the evidence supporting reported genomic variation in clinical practice.

Purpose: Genomic test results, regardless of laboratory variant classification, require clinical practitioners to judge the applicability of a variant for medical decisions. Teaching and standardizing clinical interpretation of genomic variation calls for a methodology or tool.

Methods: To generate such a tool, we distilled the Clinical Genome Resource framework of causality and the American College of Medical Genetics/Association of Molecular Pathology and Quest Diagnostic Laboratory scoring of variant deleteriousness into the Clinical Variant Analysis Tool (CVAT).

Patients benefit from mentoring students in an interprofessional health mentors program: A contextual-developmental analysis.

Purpose: Mentorship programs in health professional education are often characterized as a mutually beneficial relationship between mentor and mentee, but little is known about benefits for mentors. Mentors can be health professionals, academic faculty, other students (peers), and patients (health mentors). We studied the benefits that health mentors (people with chronic health conditions or disabilities, or a caregiver) get from mentoring students, and the contextual factors that contribute to, or explain these benefits.

Mesenteric cysts, lymphatic leak, and cerebral cavernous malformation in a proband with KRIT1-related disease.

Cerebral cavernous malformations (CCMs) of the central nervous system arise sporadically or secondary to genomic variation. Established genetic etiologies include deleterious variants in KRIT1 (CCM1), malcavernin (CCM2), and PDCD10 (CCM3). KRIT1-related disease has not been described in conjunction with lymphatic defects, although lymphatic defects with abnormal endothelial cell junctions have been observed in mice deficient in HEG1-KRIT1 signaling.