Targeting Machine Learning and Artificial Intelligence Algorithms in Health Care to Reduce Bias and Improve Population Health.

Policy Points Artificial intelligence (AI) is disruptively innovating health care and surpassing our ability to define its boundaries and roles in health care and regulate its application in legal and ethical ways. Significant progress has been made in governance in the United States and the European Union. It is incumbent on developers, end users, the public, providers, health care systems, and policymakers to collaboratively ensure that we adopt a national AI health strategy that realizes the Quintuple Aim; minimizes race-based medicine; prioritizes transparency, equity, and algorithmic vigilance; and integrates the patient and community voices throughout all aspects of AI development and deployment.

Text Mining Mental Health Reports for Issues Impacting Today's College Students: Qualitative Study.

Background: A growing number of college students are experiencing personal circumstances or encountering situations that feel overwhelming and negatively affect their academic studies and other aspects of life on campus. To meet this growing demand for counseling services, US colleges and universities are offering a growing variety of mental health services that provide support and services to students in distress.

Objective: In this study, we explore mental health issues impacting college students using a corpus of news articles, foundation reports, and media stories.

Simulation model of the relationship between cesarean section rates and labor duration.

Cesarean delivery is the most common major abdominal surgery in many parts of the world, and it accounts for nearly one-third of births in the United States. For a patient who requires a C-section, allowing prolonged labor is not recommended because of the increased risk of infection. However, for a patient who is capable of a successful vaginal delivery, performing an unnecessary C-section can have a substantial adverse impact on the patient's future health.

Diabetes and the hospitalized patient : A cluster analytic framework for characterizing the role of sex, race and comorbidity from 2006 to 2011.

In the US, one in four adults has two or more chronic conditions; this population accounts for two thirds of healthcare spending. Comorbidity, the presence of multiple simultaneous health conditions in an individual, is increasing in prevalence and has been shown to impact patient outcomes negatively. Comorbidities associated with diabetes are correlated with increased incidence of preventable hospitalizations, longer lengths of stay (LOS), and higher costs.

Online HIV awareness and technology affordance benefits for black female collegians - maybe not: the case of stigma.

Objective: We investigate the technology affordances associated with and anticipated from an online human immunodeficiency virus (HIV) prevention awareness platform, myHealthImpactNetwork, intended to reach black female college students. This population is at increased risk for HIV transmission, but is not often studied. In addition, this population regularly uses digital tools, including Web sites and social media platforms, to engage in health information seeking.

Media ownership and news framing: an analysis of HIV/AIDS coverage by Ugandan press.

Applying framing theory, the present research analyzes trends in Ugandan news coverage and the prominent issue frames for HIV/AIDS-related stories. In order to determine the influence of other factors, such as media ownership and journalist origin, nearly 800 articles, from 2000 to 2004, were gathered from the major private newspaper and government-owned newspaper in Uganda. After systematic sampling, 365 articles constitute the sample.

Modeling the impact of comorbidity on breast cancer patient outcomes.

The objective of this paper is to model the impact of comorbidity on breast cancer patient outcomes (e.g., length of stay and disposition).

Transfer and adoption of advanced information technology solutions in resource-poor environments: the case of telemedicine systems adoption in Ethiopia.

The study of the adoption of information technology (IT) by individuals has taken two approaches, one emphasizing rationalistic goal-oriented behavior and the other focusing on poignant forces that influence an individual's reaction to a new IT. These approaches are not necessarily mutually exclusive. Individuals' acceptance and subsequent usage of a new IT is predicated on both.

Telemedicine diffusion in a developing country: the case of India (March 2004).

Telemedicine (health-care delivery where physicians examine distant patients using telecommunications technologies) has been heralded as one of several possible solutions to some of the medical dilemmas that face many developing countries. In this study, we examine the current state of telemedicine in a developing country, India. Telemedicine has brought a plethora of benefits to the populace of India, especially those living in rural and remote areas (constituting about 70% of India's population).