Diabetes research and clinical practice
Dec 19, 2024
AIMS: Automated retinal image analysis using Artificial Intelligence (AI) can detect diabetic retinopathy as accurately as human graders, but it is not yet licensed in the NHS Diabetic Eye Screening Programme (DESP) in England. This study aims to ass...
With the introduction of artificial intelligence (AI) to healthcare, there is also a need for professional guidance to support its use. New (2022) reports from National Health Service AI Lab & Health Education England focus on healthcare workers' und...
In the rapidly evolving field of artificial intelligence (AI) for radiology, with a plethora of vendor options and use-cases and evidence claims to sift through, the pressing question is how to effectively implement the right tool for enhanced patien...
INTRODUCTION: A non-contrast CT head scan (NCCTH) is the most common cross-sectional imaging investigation requested in the emergency department. Advances in computer vision have led to development of several artificial intelligence (AI) tools to det...
With the increasing prevalence of artificial intelligence (AI) and other digital technologies in healthcare, the ethical debate surrounding their adoption is becoming more prominent. Here I consider the issue of gaining informed patient consent to AI...
INTRODUCTION: Coexisting multiple health conditions is common among older people, a population that is increasing globally. The potential for polypharmacy, adverse events, drug interactions and development of additional health conditions complicates ...
OBJECTIVES: Artificial intelligence (AI) is a rapidly developing field in healthcare, with tools being developed across various specialties to support healthcare professionals and reduce workloads. It is important to understand the experiences of pro...
OBJECTIVE: To compare the health-related quality of life and cost-effectiveness of robot-assisted laparoscopic surgery (RALS) versus conventional 'straight stick' laparoscopic surgery (CLS) in women undergoing hysterectomy as part of their treatment ...
OBJECTIVE: To develop an interpretable artificial intelligence algorithm to rule out normal large bowel endoscopic biopsies, saving pathologist resources and helping with early diagnosis.
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