Latest AI and machine learning research in surgery for healthcare professionals.
Hallucinations are a major concern for the integration of artificial intelligence into medicine, although less explored in the realm of medical image processing. Unlike problems in natural text understanding and reasoning therewith, determining whether or not predictions derived from biomedical images and signals is less intuitively clear. This article suggests that topological errors could consti...
Lung cancer remains one of the leading causes of cancer- related mortality worldwide. Although targeted therapies have improved outcomes for patients with non-small cell lung cancer (NSCLC), they rely on mutation profiling through tissue biopsy, an invasive procedure with several limitations. This study investigates PET/CT-based radio- genomic prediction of epidermal growth factor receptor (EGFR),...
Surgical instrument segmentation is a fundamental task for computer-assisted interventions, yet most existing methods rely on pixel-level annotations ...
Perioperative risk prediction models are often limited by narrow surgical populations, incomplete intraoperative data, poor calibration, and limited i...
Objective: To evaluate decision concordance between commercially available multimodal large language models (LLMs), resident doctors, and senior-surge...
Surgical procedures unfold as structured and recurring clinical events, whose real-time understanding via intraoperative surgical videos is critical f...
Survival analysis is an established framework for analyzing time-to-event data, yet many clinical machine learning studies still binarize the outcome ...
Ask a commercial image editor to preview a cosmetic procedure and it will often change more of the face than the request names: a nose edit can also s...
Artificial Intelligence is increasingly applied to surgical video analysis for phase segmentation, skill assessment, and workflow optimization. A key ...
Objective To evaluate the accuracy and cost of RegCheck, an automated large language model (LLM)-based workflow, for identifying clinical trial outcom...
Postoperative adverse events, including mortality and morbidity, remain a major global burden, many of which are preventable through early identificat...
Surgical gauze is an essential part of surgical procedures, primarily used for controlling bleeding and absorbing bodily fluids. The post-surgical ret...
Computed tomography angiography (CTA) is crucial for preprocedural TAVI planning, providing the anatomical information required for prosthesis sizing ...
Background: Analysis of SPES responses often relies on averaging repeated stimulation trials to improve signal quality. However, this may obscure clin...
Data augmentations define the invariances learned by self-supervised learning (SSL). Standard augmentation pipelines were designed for natural images,...
[Abstract] Objective: Intraventricular haemorrhage (IVH) carries high mortality and morbidity; accurate early prediction of 6-month functional outcome...
Background Cell free DNA (cfDNA) methylation profiling is promising for minimally invasive cancer detection, but its translation is limited by high di...
The introduction of new technologies, such as surgical robots, is driving the vision of a connected, smart operating room (OR). However, realizing thi...
Efficient surgical segmentation empowers clinical diagnosis, intraoperative monitoring, and downstream robotic pipelines for reconstruction and simula...
LLM-based database agents show promise, but differing task scopes, testbeds, and metrics hinder comparison. We identify four gaps between evaluation a...