Artificial Intelligence (AI) based clinical decision support systems to aid diagnosis are increasingly being developed and implemented but with limited understanding of how such systems integrate with existing clinical work and organizational practices. We explored the early experiences of stakeholders using an AI-based e-learning imaging software tool Veye Lung Nodules (VLN) aiding the detection, classification, and measurement of pulmonary nodules in computed tomography scans of the chest. We performed semi-structured interviews and observations across early adopter deployment sites with clinicians, strategic decision-makers, suppliers, patients with long-term chest conditions, and academics with expertise in the use of diagnostic AI in radiology settings.
View Article and Find Full Text PDFObjectives: Artificial intelligence (AI)-based clinical decision support systems to aid diagnosis are increasingly being developed and implemented but with limited understanding of how such systems integrate with existing clinical work and organizational practices. We explored the early experiences of stakeholders using an AI-based imaging software tool Veye Lung Nodules (VLN) aiding the detection, classification, and measurement of pulmonary nodules in computed tomography scans of the chest.
Materials And Methods: We performed semistructured interviews and observations across early adopter deployment sites with clinicians, strategic decision-makers, suppliers, patients with long-term chest conditions, and academics with expertise in the use of diagnostic AI in radiology settings.
Aims: The laparoscopic approach to tumour nephrectomy in children is controversial. We therefore reviewed our institution's cases of tumour nephrectomy (laparoscopic, open, and converted) to better understand which is suitable for this approach, what factors prevent it, and whether one can excise tumours greater than the CCLG recommendation of 300 ml.
Methods: All tumour nephrectomies performed between 2002 and 2016 were identified using our surgical database.
This study aimed to describe the microbiological characteristics of acute septic arthritis (SA) and osteomyelitis (OM) in children. Cases of children (0-15 years) with SA/OM were identified through a retrospective search of hospital discharge codes over a six-year period. In addition, a systematic literature search and meta-analysis of studies reporting culture results of children with SA/OM was performed.
View Article and Find Full Text PDF