Health Inequities and Structural Racism

Gallego, Damián Iglesias; Malchuk, Alexa Mieses

doi:10.1007/978-3-031-29171-5_42

Cited by 3 publications

(1 citation statement)

References 26 publications

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“…However, these tests may not be effective in detecting the early stages of COPD, leading to asymptomatic patients being less frequently tested [6]. The high cost and limited availability of spirometry, particularly in lowerincome regions, further delay diagnosis [7]. In contrast, chest radiographs (CXR) are more affordable and widely accessible.…”

Section: Introductionmentioning

confidence: 99%

Leveraging Transfer Learning for Efficient Diagnosis of COPD Using CXR Images and Explainable AI Techniques

Agughasi

2024

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Chronic Obstructive Pulmonary Disease (COPD) is a predominant global health concern, ranking third in mortality rates, yet frequently remains undiagnosed until its advanced stages. Given its prevalence, the need for innovative and widely accessible diagnostic tools has never been more paramount. While spirometry tests serve as conventional diagnostic benchmarks, their reach remains limited, especially in regions with constrained medical resources. The presented research harnesses deep learning algorithms to facilitate early-stage COPD detection, specifically targeting Chest X-rays (CXRs). The clinically annotated VinDR-CXR dataset provides the primary foundation for model training, complemented by incorporating the ChestX-ray14 dataset for initial model pre-training. Such a dual-dataset strategy augments model generalization and adaptability. Among several explored Convolutional Neural Network (CNN) architectures, the Xception model emerges as a frontrunner. Through transfer learning methodologies, this model produces a noteworthy recall rate of 98.2%, markedly surpassing the metrics of the ResNet50 model. Recognizing the imperative for transparency in AI applications in medical imaging, the research integrates essential explainability approaches viz: Gradient Class Activation Mapping (Grad-CAM) and SHapley Additive exPlanations (SHAP). These techniques elucidate the AI’s decision-making process, offering invaluable visual and analytical insights for fostering trust among medical professionals. In essence, this study not only underscores the potential of integrating AI with medical imaging for COPD detection but also accentuates the pivotal role of transparency in AI-driven medical interventions.

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Section: Introductionmentioning

confidence: 99%

Leveraging Transfer Learning for Efficient Diagnosis of COPD Using CXR Images and Explainable AI Techniques

Agughasi

2024

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Race-Based Differences in the Response to a Mindfulness Based Integrative Medical Group Visit Intervention for Chronic Pain

Incollingo Rodriguez,

Nephew,

Polcari

et al. 2024

Global Advances in Integrative Medicine and Health

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Background Chronic pain is one of the most common drivers of healthcare utilization and a marked domain for health disparities, as African American/Black populations experience high rates of chronic pain. Integrative Medical Group Visits (IMGV) combine mindfulness techniques, evidence-based integrative medicine, and medical group visits. In a parent randomized controlled trial, this approach was tested as an adjunct treatment in a diverse, medically underserved population with chronic pain and depression. Objective To determine race-based heterogeneity in the effects of a mindfulness based treatment for chronic pain. Methods This secondary analysis of the parent trial assessed heterogeneity of treatment effects along racialized identity in terms of primary patient-reported pain outcomes in a racially diverse sample suffering from chronic pain and depression. The analytic approach examined comorbidities and sociodemographics between racialized groups. RMANOVAs examined trajectories in pain outcomes (average pain, pain severity, and pain interference) over three timepoints (baseline, 9, and 21 weeks) between participants identifying as African American/Black (n = 90) vs White (n = 29) across both intervention and control conditions. Results At baseline, African American/Black participants had higher pain severity and had significantly different age, work status, and comorbidity profiles. RMANOVA models also identified significant race-based differences in the response to the parent IMGV intervention. There was reduced pain severity in African American/Black subjects in the IMGV condition from baseline to 9 weeks. This change was not observed in White participants over this time period. However, there was a reduction in pain severity in White participants over the subsequent interval from 9 to 21 week where IMGV had no significant effect in African American/Black subjects during this latter time period. Conclusion Interactions between pain and racialization require further investigation to understand how race-based heterogeneity in the response to integrative medicine treatments for chronic pain contribute to the broader landscape of health inequity.

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Social Cognition of Incarcerated Women and Children

Singh

2024

Advances in Medical Technologies and Clinical Practice

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Incarceration severely affects the health and well-being of women and their children living inside the jail. Female criminality in India has been a neglected subject of study. Due to low incidence of female criminality, there is less emphasis on research in this field. Social cognition refers to the mental processes and abilities involved in how individuals perceive, interpret, and understand the social world. This study reviews the social cognition of women prisoners and their children in jail. Women in prison constitute a special group within the prison population, first and foremost because of their sex and gender inequalities. To address these harms, comprehensive and compassionate approaches are required. Another purpose of research in this field is to create socio-political and legal awareness concerning health consequences and effective improvement in the health status of women in prison.

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Health Inequities and Structural Racism

Cited by 3 publications

References 26 publications

Leveraging Transfer Learning for Efficient Diagnosis of COPD Using CXR Images and Explainable AI Techniques

Leveraging Transfer Learning for Efficient Diagnosis of COPD Using CXR Images and Explainable AI Techniques

Race-Based Differences in the Response to a Mindfulness Based Integrative Medical Group Visit Intervention for Chronic Pain

Social Cognition of Incarcerated Women and Children

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