Publications

View details for DOI 10.1016/j.jpainsymman.2022.02.339

View details for PubMedID 35595380

View details for DOI 10.1007/s00134-021-06600-1

View details for Web of Science ID 000732505300001

View details for PubMedID 34932143

View details for DOI 10.1080/15265161.2022.2055214

View details for PubMedID 35475961

Abstract

IMPORTANCE: The development of Artificial Intelligence (AI) and other machine diagnostic systems, also known as Software as a Medical Device (SaMD), and its recent introduction into clinical practice, requires a deeply-rooted foundation in bioethics, for consideration by regulatory agencies and other stakeholders around the globe.OBJECTIVES: Initiate a dialogue on the issues to consider when developing a bioethically sound foundation for AI in medicine, based on images of eye structures, for discussion with all stakeholders.EVIDENCE REVIEW: The scope of the issues and summaries of the discussions under consideration by the Foundational Principles of Ophthalmic Imaging and Algorithmic Interpretation Working Group, as first presented during the Collaborative Community on Ophthalmic Imaging inaugural meeting on September 7, 2020, and afterwards in the working group.FINDINGS: AI has the potential to fundamentally improve the access to healthcare and patient outcomes, while decreasing disparities, lowering cost, as well as enhancing the care team. Nevertheless, substantial concerns exist. Ethicists, AI algorithm experts, as well as the Food and Drug Administration (FDA) and other regulatory agencies, industry, patient advocacy groups, clinicians and their professional societies, other provider groups, payors, and other healthcare stakeholders working together in collaborative communities to resolve such issues as non-maleficence, autonomy and equity, is essential to attain this potential, and impacts all levels of the design, validation and implementation of AI in medicine. Design, validation and implementation of AI warrant meticulous attention.CONCLUSIONS AND RELEVANCE: The development of a bioethically sound foundation may be possible if it is based in non-maleficence, autonomy and equity, for considerations for the design, validation and implementation for AI systems. Achieving such a foundation will be helpful for continuing successful introduction into medicine, before consideration by regulatory agencies around the globe.Fundamental improvements in accessibility and quality of healthcare, decrease in health disparities, and lower cost can thereby be achieved. These considerations should be discussed with all stakeholders and expanded upon as a useful initiation of this dialogue.

View details for DOI 10.1016/j.ophtha.2021.08.023

View details for PubMedID 34478784

View details for DOI 10.1097/MAT.0000000000001545

View details for PubMedID 34352820

View details for DOI 10.1038/s41591-021-01577-2

View details for PubMedID 34893774

Abstract

OBJECTIVE: To better understand diverse experts' views about the ethical implications of ongoing research funded by the National Institutes of Health that uses machine learning to predict HIV/AIDS risk in sub-Saharan Africa (SSA) based on publicly available Demographic and Health Surveys data.DESIGN: Three rounds of semi-structured surveys in an online expert panel using a modified Delphi approach.PARTICIPANTS: Experts in informatics, African public health and HIV/AIDS and bioethics were invited to participate.MEASURES: Perceived importance of or agreement about relevance of ethical issues on 5-point unipolar Likert scales. Qualitative data analysis identified emergent themes related to ethical issues and development of an ethical framework and recommendations for open-ended questions.RESULTS: Of the 35 invited experts, 22 participated in the online expert panel (63%). Emergent themes were the inclusion of African researchers in all aspects of study design, analysis and dissemination to identify and address local contextual issues, as well as engagement of communities. Experts focused on engagement with health and science professionals to address risks, benefits and communication of findings. Respondents prioritised the mitigation of stigma to research participants but recognised trade-offs between privacy and the need to disseminate findings to realise public health benefits. Strategies for responsible communication of results were suggested, including careful word choice in presentation of results and limited dissemination to need-to-know stakeholders such as public health planners.CONCLUSION: Experts identified ethical issues specific to the African context and to research on sensitive, publicly available data and strategies for addressing these issues. These findings can be used to inform an ethical implementation framework with research stage-specific recommendations on how to use publicly available data for machine learning-based predictive analytics to predict HIV/AIDS risk in SSA.

View details for DOI 10.1136/bmjopen-2021-052287

View details for PubMedID 34321310

Abstract

BACKGROUND: Digital phenotyping (also known as personal sensing, intelligent sensing, or body computing) involves the collection of biometric and personal data in situ from digital devices, such as smartphones, wearables, or social media, to measure behavior or other health indicators. The collected data are analyzed to generate moment-by-moment quantification of a person's mental state and potentially predict future mental states. Digital phenotyping projects incorporate data from multiple sources, such as electronic health records, biometric scans, or genetic testing. As digital phenotyping tools can be used to study and predict behavior, they are of increasing interest for a range of consumer, government, and health care applications. In clinical care, digital phenotyping is expected to improve mental health diagnoses and treatment. At the same time, mental health applications of digital phenotyping present significant areas of ethical concern, particularly in terms of privacy and data protection, consent, bias, and accountability.OBJECTIVE: This study aims to develop consensus statements regarding key areas of ethical guidance for mental health applications of digital phenotyping in the United States.METHODS: We used a modified Delphi technique to identify the emerging ethical challenges posed by digital phenotyping for mental health applications and to formulate guidance for addressing these challenges. Experts in digital phenotyping, data science, mental health, law, and ethics participated as panelists in the study. The panel arrived at consensus recommendations through an iterative process involving interviews and surveys. The panelists focused primarily on clinical applications for digital phenotyping for mental health but also included recommendations regarding transparency and data protection to address potential areas of misuse of digital phenotyping data outside of the health care domain.RESULTS: The findings of this study showed strong agreement related to these ethical issues in the development of mental health applications of digital phenotyping: privacy, transparency, consent, accountability, and fairness. Consensus regarding the recommendation statements was strongest when the guidance was stated broadly enough to accommodate a range of potential applications. The privacy and data protection issues that the Delphi participants found particularly critical to address related to the perceived inadequacies of current regulations and frameworks for protecting sensitive personal information and the potential for sale and analysis of personal data outside of health systems.CONCLUSIONS: The Delphi study found agreement on a number of ethical issues to prioritize in the development of digital phenotyping for mental health applications. The Delphi consensus statements identified general recommendations and principles regarding the ethical application of digital phenotyping to mental health. As digital phenotyping for mental health is implemented in clinical care, there remains a need for empirical research and consultation with relevant stakeholders to further understand and address relevant ethical issues.

View details for DOI 10.2196/27343

View details for PubMedID 34319252

View details for DOI 10.1111/bjd.21031

View details for PubMedID 35092694

Abstract

OBJECTIVE: To analyze the impact of factors in healthcare delivery on the net benefit of triggering an Advanced Care Planning (ACP) workflow based on predictions of 12-month mortality.MATERIALS AND METHODS: We built a predictive model of 12-month mortality using electronic health record data and evaluated the impact of healthcare delivery factors on the net benefit of triggering an ACP workflow based on the models' predictions. Factors included nonclinical reasons that make ACP inappropriate: limited capacity for ACP, inability to follow up due to patient discharge, and availability of an outpatient workflow to follow up on missed cases. We also quantified the relative benefits of increasing capacity for inpatient ACP versus outpatient ACP.RESULTS: Work capacity constraints and discharge timing can significantly reduce the net benefit of triggering the ACP workflow based on a model's predictions. However, the reduction can be mitigated by creating an outpatient ACP workflow. Given limited resources to either add capacity for inpatient ACP versus developing outpatient ACP capability, the latter is likely to provide more benefit to patient care.DISCUSSION: The benefit of using a predictive model for identifying patients for interventions is highly dependent on the capacity to execute the workflow triggered by the model. We provide a framework for quantifying the impact of healthcare delivery factors and work capacity constraints on achieved benefit.CONCLUSION: An analysis of the sensitivity of the net benefit realized by a predictive model triggered clinical workflow to various healthcare delivery factors is necessary for making predictive models useful in practice.

View details for DOI 10.1093/jamia/ocaa318

View details for PubMedID 33355350

Abstract

The rise of genomic technologies has catalyzed shifts in the health care landscape through the commercialization of genome sequencing and testing services in the genomics marketplace. The development of consumer genomics into a growing array of information technologies aimed at collecting, curating, and broadly sharing personal data and biological materials reconstitutes the meaning of health and reframes patients into biocitizens. In this context, the good biocitizen is expected to assume personal responsibility for health through consumption of genomic information and acquiescence to public and private efforts at data surveillance and aggregation. These shifts raise fundamental questions about how competing interests of the public, the state, and corporate entities will be reconciled and what trade-offs are demanded for the promise of precision health.

View details for DOI 10.1002/hast.1156

View details for Web of Science ID 000543918300008

View details for PubMedID 32597530

Abstract

This study describes challenges faced while incorporating sometimes conflicting stakeholder feedback into study design and development of patient-facing materials for a translational genomics study aiming to reduce health disparities among diverse populations.We conducted an ethnographic analysis of study documents including summaries of patient advisory committee meetings and interviews, reflective field notes written by study team members, and correspondence with our institutional review board (IRB). Through this analysis, we identified cross-cutting challenges for incorporating stakeholder feedback into development of our recruitment, risk assessment, and informed consent processes and materials.Our analysis revealed three key challenges: (1) balancing precision and simplicity in the design of study materials, (2) providing clinical care within the research context, and (3) emphasizing potential study benefits versus risks and limitations.While involving patient stakeholders in study design and materials development can increase inclusivity and responsiveness to patient needs, patient feedback may conflict with that of content area experts on the research team and IRBs who are tasked with overseeing the research. Our analysis highlights the need for further empirical research about ethical challenges when incorporating patient feedback into study design, and for dialogue with genomic researchers and IRB representatives about these issues.

View details for DOI 10.1038/s41436-020-0763-z

View details for PubMedID 32089547

Abstract

Background: Severe alcohol withdrawal syndrome (SAWS) is highly morbid, costly, and common among hospitalized patients, yet minimal evidence exists to guide inpatient management. Research needs in this field are broad, spanning the translational science spectrum. Goals: This research statement aims to describe what is known about SAWS, identify knowledge gaps, and offer recommendations for research in each domain of the Institute of Medicine T0-T4 continuum to advance the care of hospitalized patients who experience SAWS. Methods: Clinicians and researchers with unique and complementary expertise in basic, clinical, and implementation research related to unhealthy alcohol consumption and alcohol withdrawal were invited to participate in a workshop at the American Thoracic Society 2019 International Conference. The committee was subdivided into four groups on the basis of interest and expertise: T0-T1 (basic science research with translation to humans), T2 (research translating to patients), T3 (research translating to clinical practice), and T4 (research translating to communities). A medical librarian conducted a pragmatic literature search to facilitate this work, and committee members reviewed and supplemented the resulting evidence, identifying key knowledge gaps. Results: The committee identified several investigative opportunities to advance the care of patients with SAWS in each domain of the translational science spectrum. Major themes included 1) the need to investigate non-γ-aminobutyric acid pathways for alcohol withdrawal syndrome treatment; 2) harnessing retrospective and electronic health record data to identify risk factors and create objective severity scoring systems, particularly for acutely ill patients with SAWS; 3) the need for more robust comparative-effectiveness data to identify optimal SAWS treatment strategies; and 4) recommendations to accelerate implementation of effective treatments into practice. Conclusions: The dearth of evidence supporting management decisions for hospitalized patients with SAWS, many of whom require critical care, represents both a call to action and an opportunity for the American Thoracic Society and larger scientific communities to improve care for a vulnerable patient population. This report highlights basic, clinical, and implementation research that diverse experts agree will have the greatest impact on improving care for hospitalized patients with SAWS.

View details for DOI 10.1164/rccm.202108-1845ST

View details for Web of Science ID 000705466800002

View details for PubMedID 34609257

View details for PubMedCentralID PMC8528516

View details for Web of Science ID 000671776700003

View details for DOI 10.1177/1073110520917008

View details for PubMedID 32342787

Abstract

Applications of facial recognition technology (FRT) in health care settings have been developed to identify and monitor patients as well as to diagnose genetic, medical, and behavioral conditions. The use of FRT in health care suggests the importance of informed consent, data input and analysis quality, effective communication about incidental findings, and potential influence on patient-clinician relationships. Privacy and data protection are thought to present challenges for the use of FRT for health applications.

View details for DOI 10.1001/amajethics.2019.180

View details for PubMedID 30794128

View details for DOI 10.1038/s41746-018-0075-8

View details for Web of Science ID 000453910600001

Abstract

Self-referred imaging is one of the latest health care services to be marketed directly to consumers. Most aspects of these services are unregulated, and little is known about the messages in advertising used to attract potential consumers. We conducted a detailed analysis of print advertisements and informational brochures for self-referred imaging with respect to themes, content, accuracy, and emotional valence.Forty print advertisements from US newspapers around the country and 20 informational brochures were analyzed by 2 independent raters according to 7 major themes: health care technology; emotion, empowerment, and assurance; incentives; limited supporting evidence; popular appeal; statistics; and images. The Fisher exact test was used to identify significant differences in information content.Both the advertisements and the brochures emphasized health care and technology information and provided assurances of good health and incentives to self-refer. These materials also encouraged consumers to seek further information from company resources; virtually none referred to noncomplying sources of information or to the risks of having a scan. Images of people commonly portrayed European Americans. We found statistical differences between newspaper advertisements and mailed brochures for references to "prevalence of disease" (P<.001), "death" (P<.003), and "radiation" (P<.001). Statements lacking clear scientific evidence were identified in 38% of the advertisements (n = 15) and 25% of the brochures (n = 5).Direct-to-consumer marketing of self-referred imaging services, in both print advertisements and informational brochures, fails to provide prospective consumers with comprehensive balanced information vital to informed autonomous decision making. Professional guidelines and oversight for advertising and promotion of these services are needed.

View details for Web of Science ID 000225701900003

View details for PubMedID 15596630

Abstract

To examine different protocols for handling incidental findings on brain research MRIs, and provide a platform for establishing formal discussions of related ethical and policy issues.Corresponding authors identified from a database of peer-reviewed publications in 1991-2002 involving functional MRI (fMRI), alone or in combination with other imaging modalities, were invited to participate in this web-based survey. The survey asked questions regarding knowledge and handling of incidental findings, as well as characteristics of the scanning environment, training required, IRB protocol requirements, and neuroradiologist involvement.Seventy-four investigators who conduct MRI studies in the United States and abroad responded. Eighty-two percent (54/66) reported discovering incidental findings in their studies, such as arteriovenous malformations, brain tumors, and developmental abnormalities. Substantial variability was found in the procedures for handling and communicating findings to subjects, neuroradiologist involvement, personnel permitted to operate equipment, and training.Guidelines for minimum and optimum standards for detecting and communicating incidental findings on brain MRI research are needed.

View details for DOI 10.1002/jmri.20180

View details for Web of Science ID 000224762700001

View details for PubMedID 15503329

View details for PubMedCentralID PMC1506385

Abstract

Chylothorax is a potentially serious complication of lung and heart-lung transplantation. This article describes the clinical course of chylothorax in 3 heart-lung allograft recipients. We discuss management options, including dietary modifications, octreotide infusion, thoracic duct ligation and embolization, and surgical pleurodesis. In addition, we describe the novel use of aminocaproic acid to reduce lymph flow. We propose a multidisciplinary approach for the management of chylothorax that includes both medical and surgical options.

View details for Web of Science ID 000221393700018

View details for PubMedID 15135382

Abstract

Medical educators and researchers have increasingly sought to embed online educational modalities into graduate medical education, albeit with limited empirical evidence of how trainees perceive the value and experience of online learning in this context. The purpose of this study was to explore the experiences of hybrid learning in a graduate research methods course in a family medicine and primary care research graduate program.This qualitative description study recruited 28 graduate students during the fall 2016 academic term. Data sources included qualitative group discussions and a 76-item online survey collected between March and September 2017. We used thematic analysis and descriptive statistics to analyze each data set.Nine students took part in three group discussions, and completed an online survey. While students reported positive learning experiences overall, those attending virtually struggled with the synchronous elements of the hybrid model. Virtual students reported developing research skills not offered through courses at their home institution, and students attending the course in person benefited from the diverse perspectives of distance learners. All stressed the need to foster a sense of community.Quality delivery of online graduate education in family medicine research requires optimizing social exchanges among virtual and in-person learners, ensuring equitable engagement among all students, and leveraging the unique tools afforded by online platforms to create a shared sense of a learning community.

View details for DOI 10.22454/FamMed.2022.319716

View details for PubMedID 35675463

Abstract

Institutional review boards (IRBs) are permitted by regulation to seek assistance from outside experts when reviewing research applications that are beyond the scope of expertise represented in their membership. There is insufficient understanding, however, of when, why, and how IRBs consult with outside experts, as this practice has not been the primary focus of any published literature or empirical study to date. These issues have important implications for IRB quality. The capacity IRBs have to fulfill their mission of protecting research participants without unduly hindering research is influenced by IRBs' access to and use of the right type of expertise to review challenging research ethics, regulatory, and scientific issues. Through a review of the regulations and standards permitting IRBs to draw on the competencies of outside experts and through examination of the needs, strategies, challenges, and concerns related to doing so, we identify critical gaps in the existing literature and set forth an agenda for future empirical research.

View details for DOI 10.1002/eahr.500121

View details for PubMedID 35218600

Abstract

Poetry and medicine are related in multiple ways, including historical interests in healing, defined broadly, through words. More contemporary scholarship explores how poems, which include insights into the human condition, can enlarge our understanding of health, illness, mortality, and health care, including issues of diversity. Anesthesiology and poetry have particular affinities due to their structures, timeframes, and rhythms. Patients, physicians, and health care workers can benefit in terms of well-being by access to reading, reflecting on, and writing poetry.

View details for DOI 10.1016/j.anclin.2022.01.009

View details for PubMedID 35659407

Abstract

PURPOSE: Genomic sequencing has become an increasingly powerful and relevant tool to be leveraged for the discovery of genetic aberrations underlying rare, Mendelian conditions. Although the computational tools incorporated into diagnostic workflows for this task are continually evolving and improving, we nevertheless sought to investigate commonalities across sequencing processing workflows to reveal consensus and standard practice tools and highlight exploratory analyses where technical and theoretical method improvements would be most impactful.METHODS: We collected details regarding the computational approaches used by a genetic testing laboratory and 11 clinical research sites in the United States participating in the Undiagnosed Diseases Network via meetings with bioinformaticians, online survey forms, and analyses of internal protocols.RESULTS: We found that tools for processing genomic sequencing data can be grouped into four distinct categories. Whereas well-established practices exist for initial variant calling and quality control steps, there is substantial divergence across sites in later stages for variant prioritization and multimodal data integration, demonstrating a diversity of approaches for solving the most mysterious undiagnosed cases.CONCLUSION: The largest differences across diagnostic workflows suggest that advances in structural variant detection, noncoding variant interpretation, and integration of additional biomedical data may be especially promising for solving chronically undiagnosed cases.

View details for DOI 10.1038/s41436-020-01084-8

View details for PubMedID 33580225

Abstract

Patients with rare and undiagnosed diseases (RUDs) face significant health challenges, which may be exacerbated during the COVID-19 pandemic. The goal of this study was to identify specific impacts of the pandemic on RUD patients, and targets for improving support and health-care access.We conducted an online survey of RUD patients and their family members from 21 April to 8 June 2020, recruited from 76 Facebook groups for RUDs. Questions assessed patient characteristics and impacts of the pandemic on RUD diagnosis and management.Respondents (n = 413), including 274 RUD patients and 139 family members, were predominantly female and white, though income varied. Impacts of the pandemic included (1) barriers to accessing essential health care, (2) specific impacts of restrictive COVID-19 visitation policies on ability to advocate in health-care settings, (3) uncertainty and fear regarding COVID-19 risk, (4) exacerbated physical and mental health challenges, (5) magnified impacts of reduced educational and therapeutic services, and (6) unexpected positive changes due to the pandemic.There are specific, serious challenges affecting RUD patients and families during the COVID-19 pandemic. There is an urgent need to develop approaches to mitigate these challenges both during and beyond the pandemic.

View details for DOI 10.1038/s41436-020-01069-7

View details for PubMedID 33420343

Abstract

PURPOSE: Advances in gene therapy and precision medicine have led to a growing number of novel treatments for rare genetic diseases. Patients/families may lack access to up-to-date, accurate, and relevant information about these treatments. Social media offers one potentially important resource for these communities. Our goal was to understand how patients/families with spinal muscular atrophy (SMA)-a rare genetic condition-used social media to share, consume, and evaluate information about the novel treatment nusinersen (Spinraza) following the drug's approval.METHODS: We conducted qualitative, semistructured interviews with 20 SMA patients or parents of patients, deriving themes and subthemes through content and thematic network analysis. Participants also completed a demographic survey.RESULTS: Participants described leveraging social media to learn about nusinersen treatment, make informed treatment decisions, and advocate for/access treatment. They also described critically evaluating the trustworthiness of nusinersen-related information on social media and the privacy risks of social media use.CONCLUSION: Patients/families used social media to navigate the new and dynamic landscape of nusinersen treatment for SMA, while attempting to mitigate misinformation and privacy risks. As new treatments become available, providers and patients/families may benefit from proactively discussing social media use, so as to maximize important benefits while minimizing risks.

View details for DOI 10.1038/s41436-020-0890-6

View details for PubMedID 32601388

Abstract

INTRODUCTION: Experiences of illness change the physical body and embodiments, or the ways in which the world and the self are known through the body. When illness is anticipated, such as with inherited cancer predisposition syndromes, risk becomes embodied and shared in family groups. Embodied risk is experienced whether or not symptoms have manifested. To examine how individuals and families with genetic risk experience the world and understand their disease through their bodies, we employ Li-Fraumeni syndrome (LFS) as an exemplar. LFS is a rare, genetic, cancer predisposition syndrome with nearly 100% lifetime cancer risk starting from birth, limited opportunities for prevention, rigorous screening protocols, and early mortality.METHODS: Forty-five families, including 117 individuals aged 13-81 years, enrolled in the National Cancer Insitute's LFS study (NCT01443468) completed 66 open-ended interviews regarding LFS experiences. An interdisciplinary team used modified grounded theory to explore physical aspects of living with LFS in psychosocial contexts.FINDINGS: The physicality of living with LFS included constant monitoring of LFS bodies across the family to identify physical change that might indicate carcinogenesis. Cancer screening, risk reduction, and treatment acted as dually protective and invasive, and as an unavoidable features of LFS. Connections between family members with similar embodiments normalized aesthetic changes and supported coping with visible markers of difference. In some circumstances, participants objectified the body to preserve the self and important relationships. In others, intense pain or loss created thresholds beyond which the self could no longer be separated from the body to support coping.DISCUSSION: This paper focuses on Li-Fraumeni syndrome, a familial condition with a well-established genetic identity in which the body-self is experienced in relation to important others, to medical imaging, and to historical experiences with cancer. We expand on theories of embodied risk and inter-embodiment to describe experiences across disease trajectories, with attention to division and union between body, self, and other.

View details for DOI 10.1016/j.socscimed.2022.114905

View details for PubMedID 35367908

Abstract

Given the limited therapeutic options for most rare diseases diagnosed through genomic sequencing (GS) and the proportion of patients who remain undiagnosed even after GS, it is important to characterize a broader range of benefits and potential harms of GS from the perspectives of families with diverse sociodemographic characteristics. We recruited parents of children enrolled in the Undiagnosed Diseases Network. Parents completed an in-depth interview, and we conducted a comparative content analysis of the data. Parents (n=30) were demographically diverse, with 43.3% identifying as Hispanic, 33.3% primarily Spanish-speaking, and widely variable household income and education. Parents reported minimal changes in their child's health status following GS but did report a range of other forms of perceived utility, including improvements in their child's healthcare management and access, in their own psychological well-being, and in disease-specific social connections and research opportunities. Parents who received a diagnosis more frequently perceived utility across all domains; however, disutility also was reported by both those with and without a diagnosis. Impacts depended on multiple mediating factors, including parents' underlying expectations and beliefs, family sociodemographic characteristics, individual disease characteristics, and prior healthcare access. Our study suggests that the perceived utility of GS varies widely among parents and may depend on multiple individual, sociodemographic, and contextual factors that are relevant for pre- and post-GS counseling, for value assessment of GS, and for policymaking related to access to new genomic technologies.

View details for DOI 10.1002/ajmg.a.62619

View details for PubMedID 34981646

Abstract

Precision medicine offers a precious opportunity to change clinical practice and disrupt medicine's reliance on crude racial, ethnic, or ancestral categories by focusing on an individual's unique genetic, environmental, and lifestyle characteristics. However, precision medicine and the genomic studies that are its cornerstone have thus far failed to account for human diversity. This failure is made clearer when looking at individuals who encapsulate a mosaic of different genetic ancestries and do not fit neatly into existing population labels. This piece argues that precision medicine continues to rely on the same forms of crude categorization it seeks to unsettle. Until the scientific community creates inclusive solutions for individuals who fall outside or between our existing population labels, precision medicine will continue to fall short in its aims.

View details for DOI 10.3389/fgene.2022.795992

View details for PubMedID 35559033