International journal of MCH and AIDS
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The population with emerging diseases such as COVID-19, which is used to calculate the basic reproduction number of epidemic outbreak (R0 ) cannot be simply observed. In this article, we have proposed a method for estimating the hidden population of people with COVID-19 disease. ⋯ The provision of medical equipment (e.g., masks, alcohol, ventilators, medication, etc.), the reopening of schools and universities, the start of tourism and public gatherings, the provision of medical staff and preventive planning depend on the number of patients with the disease. Therefore, it is very important to estimate the number of patients.
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Artificial Intelligence (AI) applications in medicine have grown considerably in recent years. AI in the forms of Machine Learning, Natural Language Processing, Expert Systems, Planning and Logistics methods, and Image Processing networks provide great analytical aptitude. While AI methods were first conceptualized for radiology, investigations today are established across all medical specialties. ⋯ Other promising AI tools have demonstrated an ability to: predict burn healing time from smartphone photos; track regions of socioeconomic disparity combined with environmental trends to predict communicable disease outbreaks; and accurately predict pregnancy complications such as birth asphyxia in low resource settings with limited patient clinical data. In this commentary, we discuss the current state of AI-driven GHI and explore relevant lessons from past technology-centered GHI. Additionally, we propose a conceptual framework to guide the development of sustainable strategies for AI-driven GHI, and we outline areas for future research.
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The 2nd annual Health Equity Summer Research Summit organized by the Center of Excellence (COE) in Health Equity, Training and Research, Baylor College of Medicine (BCM), was a forum to catalyze the fertilization and exchange of cutting-edge ideas in the area of disparity research in medicine. The summit fosters understanding of current health equity research, training, clinical care, and outreach initiatives, in addition to offering an opportunity for connecting with allies and partners working in the field of health equity and health disparities. ⋯ With this summit, BCM continues to build on its long history of educational outreach initiatives to promote diversity in medicine by focusing on programs aimed at increasing the number of diverse and highly qualified medical professionals ready to introduce effective and innovative approaches to reduce or eliminate health disparities. These programs will improve information resources, clinical education, curricula, research and cultural competence as they relate to minority health issues and social determinants of health.
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Dramatic increases in opioid and drug overdose mortality have occurred in the United States (US) over the past two decades. To address this national public health crisis and identify gaps in the literature, we analyzed recent empirical trends in US drug overdose mortality by key social determinants and conducted a selective review of the recent literature on the magnitude of the opioid crisis facing different racial/ethnic, socioeconomic, and rural-urban segments of the US population. ⋯ Our analysis and review indicate substantial disparities in drug overdoses and related mortality, pain management, and treatment outcomes according to social determinants. Increases in drug overdoses and resultant mortality are not only unique to the US, but have also been observed in other industrialized countries. Healthcare systems, community leaders, and policymakers addressing the opioid epidemic should focus on upstream structural factors including education, economic opportunity, social cohesion, racial/ethnic disadvantage, geographic isolation, and life satisfaction.