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Artificial intelligence (AI) broadly describes a branch of computer science focused on developing machines capable of performing tasks typically associated with human intelligence. Those who connect AI with the world of science fiction may meet its growing rise with hesitancy or outright skepticism. However, AI is becoming increasingly pervasive in our society, from algorithms helping to sift through airline fares to substituting words in emails and SMS text messages based on user choices. Data collection is ongoing and is being leveraged by software platforms to analyze patterns and make predictions across multiple industries. Health care is gradually becoming part of this technological transformation, as advancements in computational power and storage converge with the rapid expansion of digitized medical information. Given the growing and inevitable integration of AI into health care systems, it is our viewpoint that pediatricians urgently require training and orientation to the uses, promises, and pitfalls of AI in medicine. AI is unlikely to solve the full array of complex challenges confronting pediatricians today; however, if used responsibly, it holds great potential to improve many aspects of care for providers, children, and families. Our aim in this viewpoint is to provide clinicians with a targeted introduction to the field of AI in pediatrics, including key promises, pitfalls, and clinical applications, so they can play a more active role in shaping the future impact of AI in medicine.

Maternal health outcomes have been underresearched due to people who are pregnant being underrepresented or excluded from studies based on their status as a vulnerable study population. Based on the available evidence, Black people who are pregnant have dramatically higher maternal morbidity and mortality rates compared to other racial and ethnic groups. However, insights into prenatal care-including the use of medications, immunizations, and prenatal vitamins-are not well understood for pregnant populations, particularly those that are underrepresented in biomedical research. Medication use has been particularly understudied in people who are pregnant; even though it has been shown that up to 95% of people who are pregnant take at least 1 or more medications. Understanding gaps in use could help identify ways to reduce maternal disparities and optimize maternal health outcomes. We aimed to characterize and compare the use of prenatal vitamins, immunizations, and commonly used over-the-counter and prescription medications among people who are pregnant, those self-identifying as Black versus non-Black, and those living in rural versus urban regions in the United States. We conducted a prospective, decentralized study of 4130 pregnant study participants who answered survey questionnaires using a mobile research app that was only available on iOS (Apple Inc) devices. All people who were pregnant, living in the United States, and comfortable with reading and writing in English were eligible. The study was conducted in a decentralized fashion with the use of a research app to facilitate enrollment using an eConsent and self-reported data collection. Within the study population, the use of prenatal vitamins, antiemetics, antidepressants, and pain medication varied significantly among different subpopulations underrepresented in biomedical research. Black participants reported significantly lower frequencies of prenatal vitamin use compared to non-Black participants (P<.001). The frequency of participants who were currently receiving treatment for anxiety and depression was also lower among Black and rural groups compared to their non-Black and urban counterparts, respectively. There was significantly lower use of antidepressants (P=.002) and antiemetics (P=.02) among Black compared to non-Black participants. While prenatal vitamin use was lower among participants in rural areas, the difference between rural and urban groups did not reach statistical significance (P=.08). There were no significant differences in vaccine uptake for influenza or tetanus-diphtheria-pertussis (TDaP) across race, ethnicity, rural, or urban status. A prospective, decentralized app-based study demonstrated significantly lower use of prenatal vitamins, antiemetics, and antidepressants among Black pregnant participants. Additionally, significantly fewer Black and rural participants reported receiving treatment for anxiety and depression during pregnancy. Future research dedicated to identifying the root mechanisms of these differences can help improve maternal health outcomes, specifically for diverse communities.

Although maternal morbidity and mortality in the US is among the worst of developed countries, pregnant women have been under-represented in research studies, resulting in deficiencies in evidence-based guidance for treatment. There are over two billion smartphone users worldwide, enabling researchers to easily and cheaply conduct extremely large-scale research studies through smartphone apps, especially among pregnant women in whom app use is exceptionally high, predominantly as an information conduit. We developed the first pregnancy research app that is embedded within an existing, popular pregnancy app for self-management and education of expectant mothers. Through the large-scale and simplified collection of survey and sensor generated data via the app, we aim to improve our understanding of factors that promote a healthy pregnancy for both the mother and developing fetus. From the launch of this cohort study on 16 March 2017 through 17 December 2017, we have enrolled 2058 pregnant women from all 50 states. Our study population is diverse geographically and demographically, and fairly representative of US population averages. We have collected 14,045 individual surveys and 107,102 total daily measurements of sleep, activity, blood pressure, and heart rate during this time. On average, women stayed engaged in the study for 59 days and 45 percent who reached their due date filled out the final outcome survey. During the first 9 months, we demonstrated the potential for a smartphone-based research platform to capture an ever-expanding array of longitudinal, objective, and subjective participant-generated data from a continuously growing and diverse population of pregnant women.

Women physicians do not advance in academic promotion or leadership at the same rate as their male counterparts. One factor contributing to academic promotion and advancement is the experience of serving in elected leadership positions. Although >400 women are running for political office in 2018, fewer than a handful are physicians and there has never been a woman physician elected to the Congress. Yet, little is known about women physicians who run for elected positions within their institutions, medical/professional societies, or government. This study sought to examine how women physicians experience elections using a cross-sectional survey of women physicians to gain insight into patterns of reported experiences and perceived barriers to elected leadership positions. A cross-sectional survey study of 1221 women physicians. 43.8% (N=535) of women physicians ran for an elected office from high school through medical school graduation, in contrast to only 16.7% (N=204) after graduating from medical school. Only 8.5% of women physicians surveyed reported a boss or supervisor encouraged them to run for an elected position. Women physicians are less likely to run for elected positions and for those with previous election experience, the most common barriers cited were lack of institutional time and support, experience, and mentorship.

\"Healio AI is the only model that uses only peer-reviewed studies and papers as its source in the interactive dialogue between the clinician and medical database\" The development process for Healio AI focused on survey feedback from 322 health care professionals, including 238 physicians, fielded by Healio in August. Trust in AI Survey results showed 65% of health care professionals reported some level of trust in AI Similarly, many respondents reported that their colleagues held a somewhat positive (n = 132) or neutral (n = 127) attitude toward use of AI in health care. Most respondents said they had interest in using AI tools for transcription/scribe services, to review recent literature on a specific condition or drug reaction, and for patient education materials.

Although maternal morbidity and mortality in the U.S. is among the worst of developed countries, pregnant women have been under-represented in research studies, resulting in deficiencies in evidence-based guidance for treatment. There are over two billion smartphone users worldwide, enabling researchers to easily and cheaply conduct extremely large-scale research studies through smartphone apps, especially among pregnant women in whom app use is exceptionally high, predominantly as an information conduit. We developed the first pregnancy research app that is embedded within an existing, popular pregnancy app for self-management and education of expectant mothers. Through the large-scale and simplified collection of survey and sensor generated data via the app, we aim to improve our understanding of factors that promote a healthy pregnancy for both the mother and developing fetus. From the launch of this cohort study on March 16, 2017 through December 17, 2017, we have enrolled 2,058 pregnant women from all 50 states. Our study population is diverse geographically and demographically, and fairly representative of U.S. population averages. We have collected 14,045 individual surveys and 11,669 days of sleep, activity, blood pressure and heart rate measurements during this time. On average, women stayed engaged in the study for 59 days and 45 percent who reached their due date filled out the final outcome survey. During the first nine months, we demonstrated the potential for a smartphone-based research platform to capture an ever-expanding array of longitudinal, objective and subjective participant-generated data from a continuously growing and diverse population of pregnant women.

Purpose: COVID-19-associated rhino-orbital-cerebral mucormycosis (ROCM) has reached epidemic proportion during India's second wave of COVID-19 pandemic, with several risk factors being implicated in its pathogenesis. This study aimed to determine the patient demographics, risk factors including comorbidities, and medications used to treat COVID-19, presenting symptoms and signs, and the outcome of management. Methods: This was a retrospective, observational study of patients with COVID-19-associated ROCM managed or co-managed by ophthalmologists in India from January 1, 2020 to May 26, 2021. Results: Of the 2826 patients, the states of Gujarat (22%) and Maharashtra (21%) reported the highest number of ROCM. The mean age of patients was 51.9 years with a male preponderance (71%). While 57% of the patients needed oxygen support for COVID-19 infection, 87% of the patients were treated with corticosteroids, (21% for > 10 days). Diabetes mellitus (DM) was present in 78% of all patients. Most of the cases showed onset of symptoms of ROCM between day 10 and day 15 from the diagnosis of COVID-19, 56% developed within 14 days after COVID-19 diagnosis, while 44% had delayed onset beyond 14 days. Orbit was involved in 72% of patients, with stage 3c forming the bulk (27%). Overall treatment included intravenous amphotericin B in 73%, functional endoscopic sinus surgery (FESS)/paranasal sinus (PNS) debridement in 56%, orbital exenteration in 15%, and both FESS/PNS debridement and orbital exenteration in 17%. Intraorbital injection of amphotericin B was administered in 22%. At final follow-up, mortality was 14%. Disease stage >3b had poorer prognosis. Paranasal sinus debridement and orbital exenteration reduced the mortality rate from 52% to 39% in patients with stage 4 disease with intracranial extension (p < 0.05). Conclusion: Corticosteroids and DM are the most important predisposing factors in the development of COVID-19-associated ROCM. COVID-19 patients must be followed up beyond recovery. Awareness of red flag symptoms and signs, high index of clinical suspicion, prompt diagnosis, and early initiation of treatment with amphotericin B, aggressive surgical debridement of the PNS, and orbital exenteration, where indicated, are essential for successful outcome.