An Artificial Intelligence-Based, Personalized Smartphone App to Improve Childhood Immunization Coverage and Timelines Among Children in Pakistan: Protocol for a Randomized Controlled Trial

Neonatal bioethics, AI, and genomics

Artificial intelligence (AI) and synthetic biology will transform civilization. The only question is how. In this paper, I explore some recent developments in medical AI, genomics, and synthetic biology. I speculate about the implications of these technologies for the practice of medicine and conclude that they will fundamentally alter our ideas of health, disease, medicine, and what it means to be human. I have three conclusions. First, AI and synthetic biology will force us to examine whether humanistic skills can be uniquely human and, if so, whether they are skills or natural gifts. AI will offer opportunities to examine what we mean by empathy, how we develop skills in communication, and when the human touch is essential for healing. Second, these technologies will change the ways that we will assess the value of doctors' work. Skills that can be mechanized will be devalued and delegated to machines. Doctors will either need to learn new skills or become irrelevant. Finally, AI and synthetic biology will force us to deeply examine what it means to be human. For humans to remain uniquely valuable, we will need to develop those aspects of our humanity that cannot be mechanized. Doctors will need to carefully attune themselves to the non-physical aspects of disease and suffering. Ultimately, AI and synthetic biology will force us to redesign both or systems of medical education and the systems of health care delivery in ways that meet both the medical and non-medical needs of patients.

Mobile Apps for Vaccination Services: Content Analysis and Quality Assessment

BACKGROUND

Vaccination services are increasingly in demand by the public, and mobile apps are an effective tool to meet that demand. However, the characteristics and quality of these apps are unknown.

OBJECTIVE

Commonly used vaccination service apps on the market were surveyed with regard to quality, service content, and user experience to evaluate and guide users.

METHODS

The Qimai Data mobile app data analytics platform was used to search for common vaccination service apps by keyword, and the WeChat and Alipay platforms were searched for apps. The apps included in the study were independently evaluated by two reviewers using the Mobile Application Rating Scale, and the service content and user experience of the apps were analyzed. The intragroup correlation coefficient between raters was used to measure interrater reliability.

RESULTS

In the app stores of the four major Android platforms and the iOS app store, 1092 and 207 apps were found, respectively; 189 WeChat applets and 30 Alipay applets were also found. A total of 29 apps was ultimately included in this study according to the inclusion criteria, including 21 independent apps, 4 WeChat applets, and 4 Alipay applets. Significant differences were found between independent apps and applets in terms of the quality score (t449.57=-5.301; P<.001) and the subjective quality score (z=-4.753; P<.001). No significant differences were found between iOS and Android platforms in terms of the quality score (t1404=-2.55; P=.80) and the subjective quality score (z=-0.137; P=.89). There was good intragroup consistency among the raters.

CONCLUSIONS

In this study, independent apps and nonindependent apps that rely on social and payment platforms for implementation were included in the vaccination services category. The overall quality of these apps was acceptable. Nonindependent running apps were found to have slightly lower scores and showed room for improvement, and scores for the participatory apps were found to be generally low overall.

Application of Artificial Intelligence in Combating High Antimicrobial Resistance Rates

Artificial intelligence (AI) is a branch of science and engineering that focuses on the computational understanding of intelligent behavior. Many human professions, including clinical diagnosis and prognosis, are greatly useful from AI. Antimicrobial resistance (AMR) is among the most critical challenges facing Pakistan and the rest of the world. The rising incidence of AMR has become a significant issue, and authorities must take measures to combat the overuse and incorrect use of antibiotics in order to combat rising resistance rates. The widespread use of antibiotics in clinical practice has not only resulted in drug resistance but has also increased the threat of super-resistant bacteria emergence. As AMR rises, clinicians find it more difficult to treat many bacterial infections in a timely manner, and therapy becomes prohibitively costly for patients. To combat the rise in AMR rates, it is critical to implement an institutional antibiotic stewardship program that monitors correct antibiotic use, controls antibiotics, and generates antibiograms. Furthermore, these types of tools may aid in the treatment of patients in the event of a medical emergency in which a physician is unable to wait for bacterial culture results. AI’s applications in healthcare might be unlimited, reducing the time it takes to discover new antimicrobial drugs, improving diagnostic and treatment accuracy, and lowering expenses at the same time. The majority of suggested AI solutions for AMR are meant to supplement rather than replace a doctor’s prescription or opinion, but rather to serve as a valuable tool for making their work easier. When it comes to infectious diseases, AI has the potential to be a game-changer in the battle against antibiotic resistance. Finally, when selecting antibiotic therapy for infections, data from local antibiotic stewardship programs are critical to ensuring that these bacteria are treated quickly and effectively. Furthermore, organizations such as the World Health Organization (WHO) have underlined the necessity of selecting the appropriate antibiotic and treating for the shortest time feasible to minimize the spread of resistant and invasive resistant bacterial strains.

Vaccination-hesitancy and vaccination-inequality as challenges in Pakistan's COVID-19 response

This study explores the mechanism for timely and equitable distribution of coronavirus disease 2019 (COVID-19) vaccination among the various communities in Pakistan. It examines the factors that support and/or impede peoples' access and response towards COVID-19 vaccination in Pakistan. The study uses a literature synthesis approach to examine and analyze the situation of the COVID-19 vaccination in Pakistan. The research results show "hesitancy" and "inequality" as two fundamental challenges that hinder the successful delivery of COVID-19 vaccination in Pakistan. People are reluctant to use vaccines due to conspiracy theories and religious beliefs. However, inequality, especially unequal accessibility to all social groups appears to be a more significant barrier to getting a vaccine. We argue that there is a need to mobilize community influence, social media, and mass media campaigns for public education on vaccination programs along with the engagement of religious leaders to endorse the vaccination for the masses. The area of this study is underdeveloped; thereby, future studies are recommended to investigate the possible way for equitable distribution of vaccines in multiple regions.