Showing 1,321 - 1,340 results of 8,234 for search '"healthcare"', query time: 0.19s Refine Results
  1. 1321
  2. 1322
  3. 1323

    Enhancing Chronic Disease Prediction in IoMT-Enabled Healthcare 5.0 Using Deep Machine Learning: Alzheimer’s Disease as a Case Study by Rabia Javed, Tahir Abbas, Tariq Shahzad, Khadija Kanwal, Sadaqat Ali Ramay, Muhammad Adnan Khan, Khmaies Ouahada

    Published 2025-01-01
    “…These findings have significance for tailored healthcare 5.0, enabling healthcare professionals to predict chronic disease more efficiently. …”
    Get full text
    Article
  4. 1324

    Evaluation of implementation effect of support for grassroots healthcare by nurse specialists of Traditional Chinese Medicine (中医护理专科团队下基层项目实施效果评价) by YAN Hong (颜红), ZHU Jinqing (朱进晴), WANG Huaxin (王华新), TANG Ling (唐玲)

    Published 2021-03-01
    “…Beijing Administration of Traditional Chinese Medicine had carried out the Support Work for Grassroots Healthcare by Nurse Specialists of Traditional Chinese Medicine, in order to improve the skills of Traditional Chinese Medicine nursing team in health care and level of service in hospitals of traditional Chinese and Western medicine. …”
    Get full text
    Article
  5. 1325
  6. 1326

    Local cOinage and Hospital Equipment Index (Lo Hei): projectile distance of Singapore coinage and healthcare-related equipment in a 3T magnetic resonance imaging scanner by Shao Jin Ong, James TPD Hallinan, Deborah Khoo, Desmond Hoon, Koon Liang Chia, Joanne Hang, Lycia Teo, Peijing Su, Michael Ong, Bertrand Ang, Swee Tian Quek

    Published 2024-02-01
    “…Introduction: Modern magnetic resonance imaging (MRI) scanners utilise superconducting magnets that are permanently active. Patients and healthcare professionals have been known to unintentionally introduce ferromagnetic objects into the scanning room. …”
    Get full text
    Article
  7. 1327

    Web-Based Healthcare Delivery Integrated System to Forecast COVID-19 Hospitalizations in a Marginalized Patient Population: A Case Study in Broome County, New York by Anemone Kasasbeh, Elie Issa, Naseem Khan, Mehmet Yildirim, Amy Booth, Hiroki Sayama

    Published 2024-01-01
    “…We developed a web-based integrated healthcare delivery system with a user-friendly interface to help forecast COVID-19 hospitalizations in a marginalized patient population. …”
    Get full text
    Article
  8. 1328

    Evaluating the impact of a multicountry interprofessional training programme to improve HIV knowledge and clinical confidence among healthcare workers in sub-Saharan Africa: a cohort study by Jehan Z Budak, Ian Couper, Michael Reid, Deborah von Zinkernagel, Elsie Kiguli-Malwadde, Maeve Forster, Shayanne Martin, Evelyn Chilemba, Keneilwe Motlhatlhedi, Jessica Celentano, Clara Haruzivishe, David Sears, Judy N. Khanyola, Mmoloki Molwantwa, Fred Semitala, Marietjie de Villiers, Abigail Kazembe

    Published 2022-07-01
    “…Among 188 learners (6.2%) who retook the test at >6 months, knowledge and self-reported confidence scores were greater compared with precourse scores (all p<0.05).Conclusion To our knowledge, this is the largest interprofessional, multicountry training programme established to improve HIV knowledge and clinical confidence among healthcare professional workers in SSA. The findings are notable given the size and geographical reach and demonstration of sustained confidence and knowledge retention post course completion. …”
    Get full text
    Article
  9. 1329

    SARS-CoV-2 infection and antibody seroprevalence in routine surveillance patients, healthcare workers and general population in Kita region, Mali: an observational study 2020–2021 by Ulla Ashorn, Per Ashorn, Nigel Klein, Samba O Sow, Camilla Ducker, Elaine Cloutman-Green, Dagmar Alber, Fadima Cheick Haidara, Juho Luoma, Laura Adubra, Henry Badji, Fatoumata Diallo, Rikhard Ihamuotila, Owen Martell, Uma U Onwuchekwa, Oumar Samaké, Awa Traore, Kevin Wilson, Yue-Mei Fan

    Published 2022-06-01
    “…Objective To estimate the degree of SARS-CoV-2 transmission among healthcare workers (HCWs) and general population in Kita region of Mali.Design Routine surveillance in 12 health facilities, HCWs serosurvey in five health facilities and community serosurvey in 16 villages in or near Kita town, Mali.Setting Kita region, western Mali; local health centres around the central (regional) referral health centre.Participants Patients in routine surveillance, HCWs in local health centres and community members of all ages in populations associated with study health centres.Main outcome measures Seropositivity of ELISA test detecting SARS-CoV-2-specific total antibodies and real-time RT-PCR confirmed SARS-CoV-2 infection.Results From 2392 routine surveillance samples, 68 (2.8%, 95% CI: 2.2% to 3.6%) tested positive for SARS-CoV-2 by RT-PCR. …”
    Get full text
    Article
  10. 1330

    Studio pilota di traduzione in italiano e validazione culturale di uno strumento per valutare il debriefing: il Debriefing Assessment for Simulation in Healthcare (DASH) by Sonia Lomuscio, Pierluigi Ingrassia, Andrea Mastroieni, Mauro Parozzi, Michela Bernardini, Greta Ghizzardi

    Published 2025-02-01
    “…Il Debriefing Assessment for Simulation in Healthcare (DASH) è uno strumento progettato per supportare lo sviluppo e la valutazione delle competenze di debriefing. …”
    Get full text
    Article
  11. 1331
  12. 1332
  13. 1333
  14. 1334

    Frequency, demographics, diagnoses and consultation patterns associated with low-acuity attendances in German emergency departments: a retrospective routine healthcare data analysis from the INDEED project by Patrik Dröge, Anna Slagman, Felix Greiner, Martin Möckel, Liane Schenk, Anna Schneider, Thomas Keil, Stephanie Roll, Rainer Röhrig, Felix Walcher, Reinhard Busse, Johannes Drepper, David Legg, Ryan King, Thomas Reinhold, Thomas Ruhnke, Antje Fischer-Rosinský, Yves-Noel Wu, Natalie Baier, Maike Below, Cornelia Henschke, Björn Kreye, Christian Lüpkes, Burgi Riens, Marie-Luise Rosenbusch, Felix Stäps, Kristin Schmieder, Daniel Schreiber, Dominik von Stillfried, Grit Zimmermann

    Published 2024-12-01
    “…This study aimed to estimate the frequency of low-acuity emergency department (ED) attendances and to provide an overview of their demographic, diagnosis and consultation patterns.Design Observational analyses of routine healthcare data.Setting German EDs.Participants Adult patients with statutory health insurance who visited the ED of 16 participating hospitals in 2016.Main outcome measures Frequency, demographics, diagnoses and consultation patterns of low-acuity and high-acuity attendees.Main results Of the 454 747 ED visits, 370 756 visits (50.1% female) were included for analysis. …”
    Get full text
    Article
  15. 1335

    A comparative study of machine learning algorithms for fall detection in technology-based healthcare system: Analyzing SVM, KNN, decision tree, random forest, LSTM, and CNN by Afuan Lasmedi, Isnanto R. Rizal

    Published 2025-01-01
    “…Fall detection is a major challenge in the development of technology-based healthcare systems, particularly in elderly care. This study aims to compare the performance of six classification algorithms: Support Vector Machine (SVM), K-Nearest Neighbors (KNN), Decision Tree, Random Forest, Long Short-Term Memory (LSTM), and Convolutional Neural Networks (CNN) in detecting fall incidents using wearable sensor data such as accelerometers and gyroscopes. …”
    Get full text
    Article
  16. 1336
  17. 1337

    Persistent Mortality Risk From Device-related Healthcare-associated Infection in Kidney Transplant Recipients Despite Multifaceted Interventions Action Calls for a Zero-tolerance Policy by Maria Bethânia Peruzzo, MD, Luana Oliveira Calegari, MSc, Renato Demarchi Foresto, MD, PhD, Helio Tedesco-Silva, MD, PhD, José Medina Pestana, MD, PhD, Lúcio Requião-Moura, MD, PhD

    Published 2025-02-01
    “…Although multifaceted control intervention actions (bundles) are highly effective in reducing the risk of device-related healthcare-associated infections (d-HAIs), no studies have explored their impact on the outcomes of kidney transplant recipients (KTRs) or the extent of risk reduction achievable through the bundle implementation. …”
    Get full text
    Article
  18. 1338
  19. 1339

    Development and preliminary testing of Health Equity Across the AI Lifecycle (HEAAL): A framework for healthcare delivery organizations to mitigate the risk of AI solutions worsening health inequities. by Jee Young Kim, Alifia Hasan, Katherine C Kellogg, William Ratliff, Sara G Murray, Harini Suresh, Alexandra Valladares, Keo Shaw, Danny Tobey, David E Vidal, Mark A Lifson, Manesh Patel, Inioluwa Deborah Raji, Michael Gao, William Knechtle, Linda Tang, Suresh Balu, Mark P Sendak

    Published 2024-05-01
    “…The use of data-driven technologies such as Artificial Intelligence (AI) and Machine Learning (ML) is growing in healthcare. However, the proliferation of healthcare AI tools has outpaced regulatory frameworks, accountability measures, and governance standards to ensure safe, effective, and equitable use. …”
    Get full text
    Article
  20. 1340

    Investigation Report and Analysis Knowledge, attitudes and vaccination status regarding HPV vaccines among female healthcare workers at vaccination clinics in Beijing city: a survey report by Haikun QIAN, Wenyan JI, Luodan SUO

    Published 2024-12-01
    “…MethodsIn June 2023, a self-designed online questionnaire was distributed through work groups to female healthcare workers involved in HPV vaccination services at all Beijing immunization clinics providing HPV vaccines. …”
    Get full text
    Article