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Exploring the Role of Communication Asset Mapping (CAM) as a Strategy to Promote Hereditary Cancer Risk Assessment Information Within African American Communities.
Int J Environ Res Public Health
January 2025
Department of Behavioral Science and Health Equity, College for Public Health and Social Justice, Saint Louis University, Saint Louis, MO 63103, USA.
: African Americans (AAs) carry the largest burden for almost every type of cancer in the US and are also more likely to die from cancer. Approximately 10% of cancers can be explained by a hereditary factor and detected earlier. Many AAs, however, have inequitable access to hereditary cancer risk assessment (HCRA) tools and information, further exacerbating disparities in cancer rates.
View Article and Find Full Text PDFExplainable AI in Diagnostic Radiology for Neurological Disorders: A Systematic Review, and What Doctors Think About It.
Diagnostics (Basel)
January 2025
Aerospace Engineering Department and Interdisciplinary Research Center for Smart Mobility and Logistics, and Interdisciplinary Research Center Aviation and Space Exploration, King Fahd University of Petroleum and Minerals, Dhahran 31261, Saudi Arabia.
Artificial intelligence (AI) has recently made unprecedented contributions in every walk of life, but it has not been able to work its way into diagnostic medicine and standard clinical practice yet. Although data scientists, researchers, and medical experts have been working in the direction of designing and developing computer aided diagnosis (CAD) tools to serve as assistants to doctors, their large-scale adoption and integration into the healthcare system still seems far-fetched. Diagnostic radiology is no exception.
View Article and Find Full Text PDFMachine-learning-assisted Preoperative Prediction of Pediatric Appendicitis Severity.
J Pediatr Surg
January 2025
McGill University Faculty of Medicine and Health Sciences, Canada; Harvey E. Beardmore Division of Pediatric Surgery, The Montreal Children's Hospital, McGill University Health Centre, Montreal, Qc, Canada.
Purpose: This study evaluates the effectiveness of machine learning (ML) algorithms for improving the preoperative diagnosis of acute appendicitis in children, focusing on the accurate prediction of the severity of disease.
Methods: An anonymized clinical and operative dataset was retrieved from the medical records of children undergoing emergency appendectomy between 2014 and 2021. We developed an ML pipeline that pre-processed the dataset and developed algorithms to predict 5 appendicitis grades (1 - non-perforated, 2 - localized perforation, 3 - abscess, 4 - generalized peritonitis, and 5 - generalized peritonitis with abscess).
A Next Available Appointment (NAA) Tool to Better Manage Patient Delay Risk and Patient Scheduling Expectations in Specialist Clinics.
Int J Health Plann Manage
January 2025
The Australian e-Health Research Centre, Commonwealth Scientific and Industrial Research Organisation, Melbourne, Australia.
Every year there are approximately 3 million new outpatient specialist clinic appointments at local hospital networks in Victoria, Australia. Growing daily demand for these services leads to high-volume waiting lists and therefore long appointment delays for patients. This phenomenon emphasises the importance of providing analytics and tools to assist with waiting list management in outpatient specialist clinics.
View Article and Find Full Text PDFBackground: During last ten years, we have developed a digital library with educational materials in Physical medicine and rehabilitation.
Objectives: The objective of current article is the preparation of an electronic library with educational materials in the area of physical medicine, physical therapy and rehabilitation, and the comparative evaluation of the impact of this repository on the quality of education of students and trainees in the field.
Methodology: The electronic library includes e-books on different topics, elements of the specialty "Physical and rehabilitation medicine (PRM)" or Physiatry - with theoretical data, practical issues and case reports with videos of real patients.
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