The rapid growth and diffusion of digital media technologies has changed the landscape of market segmentation in the last two decades, including its use in promoting prosocial and behavior change. New, population-specific and culturally appropriate prevention strategies can leverage the potential of digital media to influence health outcomes, especially for the greatest users of digital technology, including youth and young adults. Health behavior change campaigns are increasingly shifting resources to social media, creating opportunities for innovative interventions and new research methods. This article examines three case studies of digital segmentation: (1) tobacco control from the Truth Initiative, (2) community-based public health programs from the Centers for Disease Control and Prevention, and (3) substance use (including opioids) and other risk behavior prevention from Public Good Projects. These case studies of recent digital segmentation efforts in the not-for-profit, government, and academic sectors show that it increases reach and frequency of messages delivered to priority populations. The practice of digital segmentation is rapidly growing, shows early signs of effectiveness, and may enhance future public health campaigns. Additional research could optimize its use and effectiveness in promoting prosocial and behavior change campaign outcomes.
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http://dx.doi.org/10.1177/1090198119871246 | DOI Listing |
Sci Rep
January 2025
Department of Rehabilitation Medicine, Tongren Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200336, China.
Accurately extracting organs from medical images provides radiologist with more comprehensive evidences to clinical diagnose, which offers up a higher accuracy and efficiency. However, the key to achieving accurate segmentation lies in abundant clues for contour distinction, which has a high demand for the network architecture design and its practical training status. To this end, we design auxiliary and refined constraints to optimize the energy function by supplying additional guidance in training procedure, thus promoting model's ability to capture information.
View Article and Find Full Text PDFBMC Infect Dis
January 2025
Department of Respiratory and Critical Care Medicine, Beijing Youan Hospital, Capital Medical University, Beijing, 100069, China.
Background: Chronic pulmonary abscess usually results from bacterial or mycobacterium infection, but rarely from aspergillosis. Chronic pulmonary aspergillosis is usually found in a person with structural lung disease or immunocompromise. Here, we report a case of chronic lung abscess of aspergillosis without immunocompromise, structural lung diseases or even clinical symptoms.
View Article and Find Full Text PDFRadiology
January 2025
From the Department of Cardiology (T.P., K.H., T.G., A.L., E.G., A.U., J.G.D., P.H.), MIRACL.ai (Multimodality Imaging for Research and Analysis Core Laboratory: and Artificial Intelligence) (T.P., S.T., K.H., T.G., A.L., E.G., A.U., J.G.D., P.H.), Inserm MASCOT-UMRS 942 (T.P., K.H., T.A.S., T.G., A.L., E.G., A.U., J.G.D., P.H.), and Department of Radiology (T.P., V.B., L.H., T.G.), Université Paris Cité, University Hospital of Lariboisière, Assistance Publique-Hôpitaux de Paris, Paris, France; Cardiovascular Magnetic Resonance Laboratory (T.P., T.H., T.U., F.S., S.C., P.G., J.G.) and Cardiac Computed Tomography Laboratory (T.P., T.H., T.L., B.C., T.U., F.S., S.C., H.B., A.N., M.A., P.G., J.G.), Hôpital Privé Jacques Cartier, Institut Cardiovasculaire Paris Sud, Ramsay Santé, 6 Avenue du Noyer Lambert, 91300 Massy, France; Scientific Partnerships, Siemens Healthcare France, Saint-Denis, France (S.T.); Department of Cardiology, Hôpital Universitaire de Bruxelles-Hôpital Erasme, Brussels, Belgium (A.U.); and Department of Cardiovascular Imaging, American Hospital of Paris, Neuilly, France (O.V., M.S.).
Background Multimodality imaging is essential for personalized prognostic stratification in suspected coronary artery disease (CAD). Machine learning (ML) methods can help address this complexity by incorporating a broader spectrum of variables. Purpose To investigate the performance of an ML model that uses both stress cardiac MRI and coronary CT angiography (CCTA) data to predict major adverse cardiovascular events (MACE) in patients with newly diagnosed CAD.
View Article and Find Full Text PDFNeuroinformatics
January 2025
Neuro-Electronics Research Flanders, Kapeldreef 75, Leuven, 3001, Belgium.
The brain is composed of a dense and ramified vascular network of arteries, veins and capillaries of various sizes. One way to assess the risk of cerebrovascular pathologies is to use computational models to predict the physiological effects of reduced blood supply and correlate these responses with observations of brain damage. Therefore, it is crucial to establish a detailed 3D organization of the brain vasculature, which could be used to develop more accurate in silico models.
View Article and Find Full Text PDFNeurosurg Rev
January 2025
Department of Neurosurgery, Policlinico Umberto I, Sapienza University of Rome, Rome, Italy.
To explore temporal dynamics of cerebral herniation through the calvarial defect after decompressive craniectomy. To investigate patterns of hemispheric asymmetry in ischemic stroke and traumatic brain injury after decompressive craniectomy.To assess clinical implications of hemispheric asymmetry evaluation in order to minimize cranioplasty complications.
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