Automated capture of intraoperative adverse events using artificial intelligence: a systematic review and meta-analysis

MB Eppler, AS Sayegh, M Maas, A Venkat… - Journal of Clinical …, 2023 - mdpi.com
Intraoperative adverse events (iAEs) impact the outcomes of surgery, and yet are not
routinely collected, graded, and reported. Advancements in artificial intelligence (AI) have …

[HTML][HTML] Multi-scale feature retention and aggregation for colorectal cancer diagnosis using gastrointestinal images

A Haider, M Arsalan, SH Nam, JS Hong… - … Applications of Artificial …, 2023 - Elsevier
Colonoscopy is considered the gold standard for colorectal cancer diagnosis and prognosis.
However, existing methods are less accurate and prone to overlooking lesions during …

[HTML][HTML] DSRD-Net: Dual-stream residual dense network for semantic segmentation of instruments in robot-assisted surgery

T Mahmood, SW Cho, KR Park - Expert Systems with Applications, 2022 - Elsevier
In conventional robot-assisted minimally invasive procedures (RMIS), surgeons have narrow
visual and complex working spaces, along with specular reflection, blood, camera-lens …

Robust real-time detection of laparoscopic instruments in robot surgery using convolutional neural networks with motion vector prediction

K Jo, Y Choi, J Choi, JW Chung - Applied Sciences, 2019 - mdpi.com
More than half of post-operative complications can be prevented, and operation
performances can be improved based on the feedback gathered from operations or …

[HTML][HTML] CFFR-Net: A channel-wise features fusion and recalibration network for surgical instruments segmentation

T Mahmood, JS Hong, N Ullah, SJ Lee, A Wahid… - … Applications of Artificial …, 2023 - Elsevier
Surgical instrument segmentation plays a crucial role in robot-assisted surgery by furnishing
essential information about instrument location and orientation. This information not only …

Intraoperative adverse event detection in laparoscopic surgery: Stabilized multi-stage temporal convolutional network with focal-uncertainty loss

H Wei, F Rudzicz, D Fleet… - Machine Learning …, 2021 - proceedings.mlr.press
Intraoperative adverse events (iAEs) increase rates of postoperative mortality and morbidity.
Identifying iAEs is important to quality assurance and postoperative care, but requires …

PaI‐Net: A modified U‐Net of reducing semantic gap for surgical instrument segmentation

X Wang, L Wang, X Zhong, C Bai, X Huang… - IET Image …, 2021 - Wiley Online Library
Tracking the instruments in a surgical scene is an essential task in minimally invasive
surgery. However, due to the unpredictability of scenes, automatically segmenting the …

Autonomous neurosurgical instrument segmentation using end-to-end learning

N Kalavakonda, B Hannaford… - Proceedings of the …, 2019 - openaccess.thecvf.com
Monitoring surgical instruments is an essential task in computer-assisted interventions and
surgical robotics. It is also important for navigation, data analysis, skill assessment and …

Real-time detection of active bleeding in laparoscopic colectomy using artificial intelligence

K Horita, K Hida, Y Itatani, H Fujita, Y Hidaka… - Surgical …, 2024 - Springer
Background Most intraoperative adverse events (iAEs) result from surgeons' errors, and
bleeding is the majority of iAEs. Recognizing active bleeding timely is important to ensure …

[HTML][HTML] Assessment of Automated Identification of Phases in Videos of Total Hip Arthroplasty Using Deep Learning Techniques

YJ Kang, SJ Kim, SH Seo, S Lee, HS Kim… - Clinics in Orthopedic …, 2024 - ncbi.nlm.nih.gov
Background As the population ages, the rates of hip diseases and fragility fractures are
increasing, making total hip arthroplasty (THA) one of the best methods for treating elderly …