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Medical Imaging Data Strategies for Catalyzing AI Medical Device Innovation.
J Imaging Inform Med
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Office of Science and Engineering Laboratories, Center for Devices and Radiological Health, U.S. Food and Drug Administration, 10903 New Hampshire Ave, Silver Spring, MD, 20993, USA.
Continuous and consistent access to quality medical imaging data stimulates innovations in artificial intelligence (AI) technologies for patient care. Breakthrough innovations in data-driven AI technologies are founded on seamless communication between data providers, data managers, data users and regulators or other evaluators to determine the standards for quality data. However, the complexity in imaging data quality and heterogeneous nature of AI-enabled medical devices and their intended uses presents several challenges limiting the clinical translation of novel AI technologies.
View Article and Find Full Text PDFPembrolizumab added to neoadjuvant chemotherapy may improve pathological complete response in androgen-receptor positive and low tumor-infiltrating lymphocytes triple-negative breast cancer patients.
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Tepe Prime, MKA Breast Cancer Clinic, 06800, Ankara, Turkey.
Is there a mental health diagnostic crisis in primary care? Current research practices in global mental health cannot answer that question.
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Health Service and Population Research Department, Institute of Psychiatry, Psychology and Neuroscience, Center for Global Mental Health, King's College London, London, UK.
In low- and middle-income countries, fewer than 1 in 10 people with mental health conditions are estimated to be accurately diagnosed in primary care. This is despite more than 90 countries providing mental health training for primary healthcare workers in the past two decades. The lack of accurate diagnoses is a major bottleneck to reducing the global mental health treatment gap.
View Article and Find Full Text PDFQuantitative approaches to structural intersectionality research: Conceptual and methodologic considerations.
Soc Sci Med
January 2025
Division of Adolescent and Young Adult Medicine, Boston Children's Hospital, Boston, MA, USA; Department of Pediatrics, Harvard Medical School, Boston, MA, USA.
There has been a recent influx in the development of novel measures of structural forms of discrimination, including structural racism, xenophobia, sexism, heterosexism, and cisgenderism. These systems of power and oppression are inherently interdependent and mutually constitutive, yet a paucity of research has investigated their joint impacts; this gap is likely reflective of the limited guidance that exists regarding how to effectively combine multiple measures of structural discrimination to examine their joint impacts on population health and health inequities. In this commentary, we seek to redress this by describing conceptual and methodologic considerations for population health researchers interested in conducting quantitative structural intersectionality research - an intersectionality-informed research approach focused on examining how systems of power and oppression intersect to shape population health and health inequities.
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