RESUMO
The role of physicians has always been to synthesize the data available to them to identify diagnostic patterns that guide treatment and follow response. Today, increasingly sophisticated machine learning algorithms may grow to support clinical experts in some of these tasks. Machine learning has the potential to benefit patients and cardiologists, but only if clinicians take an active role in bringing these new algorithms into practice. The aim of this review is to introduce clinicians who are not data science experts to key concepts in machine learning that will allow them to better understand the field and evaluate new literature and developments. The current published data in machine learning for cardiovascular disease is then summarized, using both a bibliometric survey, with code publicly available to enable similar analysis for any research topic of interest, and select case studies. Finally, several ways that clinicians can and must be involved in this emerging field are presented.
Assuntos
Cardiologia , Aprendizado de Máquina , HumanosRESUMO
Lesbian, gay, bisexual, transgender, queer, and other sexual/gender minority (LGBTQ+) health care providers face both general work-related stresses and working in heteronormative settings with ill-informed or hostile coworkers and patients, yet there has been little study of whether the coping strategies are specific to LGBTQ+ stress. We analyzed qualitative data from 277 health care professionals. Sources of stress included religiously and politically conservative coworkers, coworker/patient lack of knowledge, stresses of being closeted, and concerns about being out to patients. Consequences of being out as LGBTQ+ included lack of promotions, gossip, refusals of tenure, and anti-LGBTQ+ comments and behaviors in the workplace. Respondents showed mostly positive coping strategies to deal with stress, including becoming educators/advocates and self-care activities. Self-care options were common in rural areas with few LGBTQ+ social resources. Negative coping strategies were reported by 18% of respondents. The study highlights the extra burden of stress on LGBTQ+ health care providers.