Geneva Foundation for Medical Education and Research.
Published: January 2018
AI Article Synopsis
Article Abstract
Objectives: Colposcopes are expensive, heavy, and need specialized technical service, which may outreach the capacity of low-resource settings. Our aim was to assess the performance of smartphone-based digital images for the detection of cervical intraepithelial neoplasia grade 2 or worse (CIN2+).
Methods: Human papillomavirus (HPV)-positive women recruited through a cervical cancer screening campaign had VIA/VILI assessment (visual inspection after application of acetic acid/lugol's iodine). Cervical digital images were captured with a smartphone camera, randomly coded with no prior selection and distributed on an online database (Google Forms) for evaluation. Healthcare providers were invited to evaluate the images and identify CIN2+. The gold standard was the histopathological diagnosis. The sensitivity and specificity for the detection of CIN2+ was assessed for each reader and reported with the 95 percent confidence interval (Clopper-Pearson method).
Results: One hundred twenty-five consecutive HPV-positive women were included, with 19 CIN2+ (15.2 percent). Forty-five gynecologists completed the assessment, one-third were considered as experts (>50 colposcopies) and two-thirds as novices (<50 colposcopies). The sensitivity and specificity for CIN 2+ detection was 71.3 percent (67.0-75.7 percent) and 62.4 percent (57.5-67.4 percent), respectively. The performance of novices and experts was similar. The readers assessed 73.1 percent of images as acceptable for diagnostic.
Conclusion: Smartphone-based digital images, with its high portability, have a great potential for the diagnosis of CIN2+ in low-resource context.
Background/aims: Alzheimer's Disease (AD) is a progressive neurodegenerative disorder that severely affects cognitive functions and memory. Early detection is crucial for timely intervention and improved patient outcomes. However, traditional diagnostic tools, such as MRI and PET scans, are costly and less accessible.
Improved surgical skill is generally associated with improved patient outcomes, although assessment is subjective, labour intensive, and requires domain-specific expertise. Automated data-driven metrics can alleviate these difficulties, as demonstrated by existing machine learning instrument tracking models. However, these models are tested on limited datasets of laparoscopic surgery, with a focus on isolated tasks and robotic surgery.
Patient-specific implant placement in the case of pelvic tumour resection is usually a complex procedure, where the planned optimal position of the prosthesis may differ from the final location. This discrepancy arises from incorrect or differently executed bone resection and improper final positioning of the prosthesis. In order to overcome such mismatch, a navigation solution is presented based on an augmented reality application for HoloLens 2 to assist the entire procedure.
During the Russia-Ukraine war, Ukrainian President Volodymyr Zelenskyy has strategically used social media to appeal for international support. This reflects a broader trend of political figures relying on digital platforms to shape public opinion and influence global narratives during crises. This work uses three main analysis methods, content, sentiment and social network analysis.
Advancements in noninvasive surface and internal imaging techniques, along with computational methods, have revolutionized 3D visualization of organismal morphology-enhancing research, medical anatomical analysis, and facilitating the preservation and digital archiving of scientific specimens. We introduce the SmARTR pipeline (Small Animal Realistic Three-dimensional Rendering), a comprehensive workflow integrating wet lab procedures, 3D data acquisition, and processing to produce photorealistic scientific data through 3D cinematic rendering. This versatile pipeline supports multiscale visualizations-from tissue-level to whole-organism details across diverse living organisms-and is adaptable to various imaging sources.
