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Artificial intelligence (AI) and machine learning are central components of today's medical environment. The fairness of AI, i.e. the ability of AI to be free from bias, has repeatedly come into question. This study investigates the diversity of members of academia whose scholarship poses questions about the fairness of AI. The articles that combine the topics of fairness, artificial intelligence, and medicine were selected from Pubmed, Google Scholar, and Embase using keywords. Eligibility and data extraction from the articles were done manually and cross-checked by another author for accuracy. Articles were selected for further analysis, cleaned, and organized in Microsoft Excel; spatial diagrams were generated using Public Tableau. Additional graphs were generated using Matplotlib and Seaborn. Linear and logistic regressions were conducted using Python to measure the relationship between funding status, number of citations, and the gender demographics of the authorship team. We identified 375 eligible publications, including research and review articles concerning AI and fairness in healthcare. Analysis of the bibliographic data revealed that there is an overrepresentation of authors that are white, male, and are from high-income countries, especially in the roles of first and last author. Additionally, analysis showed that papers whose authors are based in higher-income countries were more likely to be cited more often and published in higher impact journals. These findings highlight the lack of diversity among the authors in the AI fairness community whose work gains the largest readership, potentially compromising the very impartiality that the AI fairness community is working towards., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Alberto et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Competing Interests: I have read the journal’s policy and the authors of this manuscript have the following competing interests: ABM serves as the executive director of the Asia eHealth Information Network and senior vice-president of St Luke’s Medical Center.

Non-fungible tokens (NFTs) are cryptographic assets recorded on the blockchain that can certify authenticity and ownership, and they can be used to monetize health data, optimize the process of receiving a hematopoietic stem cell transplant, and improve the distribution of solid organs for transplantation. Blockchain technology, including NFTs, provides equitable access to wealth, increases transparency, eliminates personal or institutional biases of intermediaries, reduces inefficiencies, and ensures accountability. Blockchain architecture is ideal for ensuring security and privacy while granting individuals jurisdiction over their own information, making it a unique solution to the current limitations of existing health information systems. NFTs can be used to give patients the option to monetize their health data and provide valuable data to researchers. Wearable technology companies can also give their customers the option to monetize their data while providing data necessary to improve their products. Additionally, the process of receiving a hematopoietic stem cell transplant and the distribution of solid organs for transplantation could benefit from the integration of NFTs into the allocation process. However, there are limitations to the technology, including high energy consumption and the need for regulatory guidance. Further research is necessary to fully understand the potential of NFTs in healthcare and how it can be integrated with existing health information technology. Overall, NFTs have the potential to revolutionize the healthcare sector, providing benefits such as improved access to health information and increased efficiency in the distribution of organs for transplantation., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Yaghy et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

As the health-care industry emerges into a new era of digital health driven by cloud data storage, distributed computing, and machine learning, health-care data have become a premium commodity with value for private and public entities. Current frameworks of health data collection and distribution, whether from industry, academia, or government institutions, are imperfect and do not allow researchers to leverage the full potential of downstream analytical efforts. In this Health Policy paper, we review the current landscape of commercial health data vendors, with special emphasis on the sources of their data, challenges associated with data reproducibility and generalisability, and ethical considerations for data vending. We argue for sustainable approaches to curating open-source health data to enable global populations to be included in the biomedical research community. However, to fully implement these approaches, key stakeholders should come together to make health-care datasets increasingly accessible, inclusive, and representative, while balancing the privacy and rights of individuals whose data are being collected., Competing Interests: Declaration of interests We declare no competing interests., (Copyright © 2023 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. Published by Elsevier Ltd.. All rights reserved.)

Competing Interests: The authors declare no conflicts of interest.

Diagnostics, including laboratory tests, medical and nuclear imaging, and molecular testing, are essential in the diagnosis and management of cancer to optimize clinical outcomes. With the continuous rise in cancer mortality and morbidity in the Association of Southeast Asian Nations (ASEAN), there exists a critical need to evaluate the accessibility of cancer diagnostics in the region so as to direct multifaceted interventions that will address regional inequities and inadequacies in cancer care. This paper identifies existing gaps in service delivery, health workforce, health information systems, leadership and governance, and financing and how these contribute to disparities in access to cancer diagnostics in ASEAN member countries. Intersectoral health policies that will strengthen coordinated laboratory services, upscale infrastructure development, encourage health workforce production, and enable proper appropriation of funding are necessary to effectively reduce the regional cancer burden., Competing Interests: BAM received research grants from the 10.13039/100000892Prostate Cancer Foundation, the 10.13039/100001960American Society for Radiation Oncology, the United States 10.13039/100000005Department of Defense, and the 10.13039/100018896Sylvester Comprehensive Cancer Center. ECD is funded in part through the Cancer Center Support Grant from the National Cancer Institute (P30 CA008748). All other authors declare no conflicts of interest., (© 2023 The Authors.)

Competing Interests: JPAC currently serves as the vice president of the Philippine Radiation Oncology Society. All other authors declare no competing interests.

Introduction: In March 2020, the coronavirus disease 2019 (COVID-19) pandemic forced medical schools in the Philippines to stop face-to-face learning activities and abruptly shift to an online curriculum. This study aimed to identify barriers to online learning from the perspective of medical students in a developing country., Methods: The authors sent out an electronic survey to medical students in the Philippines from 11 to 24 May 2020. Using a combination of multiple-choice, Likert scale, and open-ended questions, the following data were obtained: demographics, medical school information, access to technological resources, study habits, living conditions, self-assessment of capacity for and perceived barriers to online learning, and proposed interventions. Descriptive statistics were calculated. Responses were compared between student subgroups using nonparametric tests., Results: Among 3670 medical students, 93% owned a smartphone and 83% had a laptop or desktop computer. To access online resources, 79% had a postpaid internet subscription while 19% used prepaid mobile data. Under prevailing conditions, only 1505 students (41%) considered themselves physically and mentally capable of engaging in online learning. Barriers were classified under five categories: technological, individual, domestic, institutional, and community barriers., Discussion: Medical students in the Philippines confronted several interrelated barriers as they tried to adapt to online learning. Most frequently encountered were difficulty adjusting learning styles, having to perform responsibilities at home, and poor communication between educators and learners. By implementing student-centered interventions, medical schools and educators play a significant role in addressing these challenges during the COVID-19 pandemic and beyond., Supplementary Information: The online version contains supplementary material available at 10.1007/s40670-021-01231-z., Competing Interests: Conflict of InterestThe authors declare that they have no conflict of interest., (© International Association of Medical Science Educators 2021.)