Fiona R. Kolbinger
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View article: Artificial intelligence for surgical scene understanding: a systematic review and reporting quality meta-analysis
Artificial intelligence for surgical scene understanding: a systematic review and reporting quality meta-analysis Open
Surgical scene understanding (SSU) uses artificial intelligence (AI) to interpret visual data from surgeries, such as laparoscopic videos. Despite promising foundational research on instrument and anatomy recognition, clinical adoption rem…
View article: A Decade of C3 Glomerulopathy—A Nationwide Cohort Study
A Decade of C3 Glomerulopathy—A Nationwide Cohort Study Open
View article: Current validation practice undermines surgical AI development
Current validation practice undermines surgical AI development Open
Surgical data science (SDS) is rapidly advancing, yet clinical adoption of artificial intelligence (AI) in surgery remains severely limited, with inadequate validation emerging as a key obstacle. In fact, existing validation practices ofte…
View article: Federated Learning for Surgical Vision in Appendicitis Classification: Results of the FedSurg EndoVis 2024 Challenge
Federated Learning for Surgical Vision in Appendicitis Classification: Results of the FedSurg EndoVis 2024 Challenge Open
Purpose: The FedSurg challenge was designed to benchmark the state of the art in federated learning for surgical video classification. Its goal was to assess how well current methods generalize to unseen clinical centers and adapt through …
View article: Decentralized, privacy-preserving surgical video analysis with Swarm Learning
Decentralized, privacy-preserving surgical video analysis with Swarm Learning Open
Background Progress in artificial intelligence-based analysis of surgical videos has been constrained by reliance on manual frame-level annotations rather than patient-level outcomes. In addition, concerns about data privacy restrict the e…
View article: #2442 Ten years of C3 glomerulopathy: a nationwide cohort study
#2442 Ten years of C3 glomerulopathy: a nationwide cohort study Open
Background and Aims C3 glomerulopathy (C3G) is a rare but potentially devastating disease affecting both children and adults. It frequently leads to kidney failure within ten years after diagnosis and currently no specific treatment exists…
View article: Histopathological evaluation of abdominal aortic aneurysms with deep learning
Histopathological evaluation of abdominal aortic aneurysms with deep learning Open
View article: Appendix300: A multi-institutional laparoscopic appendectomy video dataset for computational modeling tasks
Appendix300: A multi-institutional laparoscopic appendectomy video dataset for computational modeling tasks Open
Structured Abstract Background The limited availability of diverse and representative training data poses a critical barrier to the development of clinically relevant computational tools for intraoperative surgical decision support. Surgic…
View article: Translationale Herausforderungen und klinisches Potenzial von künstlicher Intelligenz in der minimal-invasiven Chirurgie
Translationale Herausforderungen und klinisches Potenzial von künstlicher Intelligenz in der minimal-invasiven Chirurgie Open
Zusammenfassung Künstliche Intelligenz (KI) bietet enormes Potenzial für die Chirurgie. Anwendungsfelder reichen von interdisziplinärer Therapiestratifizierung über die Unterstützung der Operationsplanung bis zur Entscheidungsunterstützung…
View article: Postoperative complication management: How do large language models measure up to human expertise?
Postoperative complication management: How do large language models measure up to human expertise? Open
Managing postoperative complications is an essential part of surgical care and largely depends on the medical team’s experience. Large Language Models (LLMs) have demonstrated immense potential in supporting medical professionals. To evalu…
View article: Pancreatoduodenectomy versus total pancreatectomy and simultaneous intraportal islet autotransplantation for periampullary cancer at high-risk of postoperative pancreatic fistula (XANDTX-trial): Protocol of a randomized controlled pilot trial
Pancreatoduodenectomy versus total pancreatectomy and simultaneous intraportal islet autotransplantation for periampullary cancer at high-risk of postoperative pancreatic fistula (XANDTX-trial): Protocol of a randomized controlled pilot trial Open
Introduction Pancreatic surgery remains associated with significant morbidity. Pancreatoduodenectomy (PD) with high-risk stigmata for postoperative pancreatic fistula (POPF) may delay or hinder administration of adjuvant therapy. Total pan…
View article: Prompt injection attacks on vision-language models for surgical decision support
Prompt injection attacks on vision-language models for surgical decision support Open
Importance Artificial Intelligence-driven analysis of laparoscopic video holds potential to increase the safety and precision of minimally invasive surgery. Vision-language models are particularly promising for video-based surgical decisio…
View article: Artificial intelligence in pancreatic intraductal papillary mucinous neoplasm imaging: A systematic review
Artificial intelligence in pancreatic intraductal papillary mucinous neoplasm imaging: A systematic review Open
Based on the Fukuoka and Kyoto international consensus guidelines, the current clinical management of intraductal papillary mucinous neoplasm (IPMN) largely depends on imaging features. While these criteria are highly sensitive in detectin…
View article: Vision-language models for automated video analysis and documentation in laparoscopic surgery: a proof-of-concept study
Vision-language models for automated video analysis and documentation in laparoscopic surgery: a proof-of-concept study Open
Background: The ongoing shortage of medical personnel highlights the urgent need to automate clinical documentation and reduce administrative burden. Large vision-language models (VLMs) offer promising potential for supporting surgical doc…
View article: Artificial Intelligence for Surgical Scene Understanding: A Systematic Review and Reporting Quality Meta-Analysis
Artificial Intelligence for Surgical Scene Understanding: A Systematic Review and Reporting Quality Meta-Analysis Open
Surgical scene understanding (SSU) describes the use of Artificial Intelligence (AI) to provide an understanding of visual components of surgical imaging data, such as laparoscopic surgery videos. While hundreds of publications report AI c…
View article: Challenging Vision-Language Models with Surgical Data: A New Dataset and Broad Benchmarking Study
Challenging Vision-Language Models with Surgical Data: A New Dataset and Broad Benchmarking Study Open
While traditional computer vision models have historically struggled to generalize to endoscopic domains, the emergence of foundation models has shown promising cross-domain performance. In this work, we present the first large-scale study…
View article: Mission Balance: Generating Under-represented Class Samples using Video Diffusion Models
Mission Balance: Generating Under-represented Class Samples using Video Diffusion Models Open
Computer-assisted interventions can improve intra-operative guidance, particularly through deep learning methods that harness the spatiotemporal information in surgical videos. However, the severe data imbalance often found in surgical vid…
View article: Federated EndoViT: Pretraining Vision Transformers via Federated Learning on Endoscopic Image Collections
Federated EndoViT: Pretraining Vision Transformers via Federated Learning on Endoscopic Image Collections Open
Purpose: In this study, we investigate the training of foundation models using federated learning to address data-sharing limitations and enable collaborative model training without data transfer for minimally invasive surgery. Methods: In…
View article: AutoFRS: an externally validated, annotation-free approach to computational preoperative complication risk stratification in pancreatic surgery – an experimental study
AutoFRS: an externally validated, annotation-free approach to computational preoperative complication risk stratification in pancreatic surgery – an experimental study Open
Background: The risk of postoperative pancreatic fistula (POPF), one of the most dreaded complications after pancreatic surgery, can be predicted from preoperative imaging and tabular clinical routine data. However, existing studies suffer…
View article: Benchmarking Vision Capabilities of Large Language Models in Surgical Examination Questions
Benchmarking Vision Capabilities of Large Language Models in Surgical Examination Questions Open
GPT-4 demonstrated substantial capabilities in answering surgical text and image exam questions. Therefore, it holds considerable potential for the use in surgical decision making and education of students and trainee surgeons.
View article: From marginal gains to clinical utility: machine learning–based percutaneous coronary intervention risk prediction models
From marginal gains to clinical utility: machine learning–based percutaneous coronary intervention risk prediction models Open
View article: Artificial Intelligence in Pancreatic Intraductal Papillary Mucinous Neoplasm Imaging: A Systematic Review
Artificial Intelligence in Pancreatic Intraductal Papillary Mucinous Neoplasm Imaging: A Systematic Review Open
Background Based on the Fukuoka and Kyoto international consensus guidelines, the current clinical management of intraductal papillary mucinous neoplasm (IPMN) largely depends on imaging features. While these criteria are highly sensitive …
View article: The performance of artificial intelligence on a national medical licensing examination—the answers of large language models to text questions
The performance of artificial intelligence on a national medical licensing examination—the answers of large language models to text questions Open
View article: Data Augmentation for Surgical Scene Segmentation with Anatomy-Aware Diffusion Models
Data Augmentation for Surgical Scene Segmentation with Anatomy-Aware Diffusion Models Open
In computer-assisted surgery, automatically recognizing anatomical organs is crucial for understanding the surgical scene and providing intraoperative assistance. While machine learning models can identify such structures, their deployment…
View article: SeeSaw: Learning Soft Tissue Deformation From Laparoscopy Videos With GNNs
SeeSaw: Learning Soft Tissue Deformation From Laparoscopy Videos With GNNs Open
A major challenge in image-guided laparoscopic surgery is that structures of interest often deform and go, even if only momentarily, out of view. Methods which rely on having an up-to-date impression of those structures, such as registrati…
View article: One model to use them all: training a segmentation model with complementary datasets
One model to use them all: training a segmentation model with complementary datasets Open
View article: Histopathological evaluation of abdominal aortic aneurysms with deep learning
Histopathological evaluation of abdominal aortic aneurysms with deep learning Open
Computational analysis of histopathological specimens holds promise in identifying biomarkers, elucidating disease mechanisms, and streamlining clinical diagnosis. However, the application of deep learning techniques in vascular pathology …
View article: Reporting guidelines in medical artificial intelligence: a systematic review and meta-analysis
Reporting guidelines in medical artificial intelligence: a systematic review and meta-analysis Open
View article: Strategies to Improve Real-World Applicability of Laparoscopic Anatomy Segmentation Models
Strategies to Improve Real-World Applicability of Laparoscopic Anatomy Segmentation Models Open
Accurate identification and localization of anatomical structures of varying size and appearance in laparoscopic imaging are necessary to leverage the potential of computer vision techniques for surgical decision support. Segmentation perf…
View article: One model to use them all: Training a segmentation model with complementary datasets
One model to use them all: Training a segmentation model with complementary datasets Open
Understanding a surgical scene is crucial for computer-assisted surgery systems to provide any intelligent assistance functionality. One way of achieving this scene understanding is via scene segmentation, where every pixel of a frame is c…