Surgery

Parathyroid gland identification and angiography classification using simple machine learning methods.

BACKGROUND: Near-infrared indocyanine green angiography allows experienced surgeons to reliably evaluate parathyroid gland vitality during thyroid and parathyroid operations in order to predict postoperative function. To facilitate equal performance between surgeons, we developed an automatic computational quantification method using computer vision that portrays expert interpretation of visualize...

Presurgical Upgrade Prediction of DCIS to Invasive Ductal Carcinoma Using Time-dependent Deep Learning Models with DCE MRI.

Purpose To determine whether time-dependent deep learning models can outperform single time point models in predicting preoperative upgrade of ductal carcinoma in situ (DCIS) to invasive malignancy at dynamic contrast-enhanced (DCE) breast MRI without a lesion segmentation prerequisite. Materials and Methods In this exploratory study, 154 cases of biopsy-proven DCIS (25 upgraded at surgery and 129...

Artificial Intelligence Outcome Prediction in Neonates with Encephalopathy (AI-OPiNE).

Purpose To develop a deep learning algorithm to predict 2-year neurodevelopmental outcomes in neonates with hypoxic-ischemic encephalopathy using MRI ...

Deep Learning to Detect Intracranial Hemorrhage in a National Teleradiology Program and the Impact on Interpretation Time.

The diagnostic performance of an artificial intelligence (AI) clinical decision support solution for acute intracranial hemorrhage (ICH) detection was...

Deep Learning Segmentation of Infiltrative and Enhancing Cellular Tumor at Pre- and Posttreatment Multishell Diffusion MRI of Glioblastoma.

Purpose To develop and validate a deep learning (DL) method to detect and segment enhancing and nonenhancing cellular tumor on pre- and posttreatment ...

Does artificial intelligence predict orthognathic surgical outcomes better than conventional linear regression methods?

OBJECTIVES: To evaluate the performance of an artificial intelligence (AI) model in predicting orthognathic surgical outcomes compared to conventional...

PolicyLR: A Logic Representation For Privacy Policies

Privacy policies are crucial in the online ecosystem, defining how services handle user data and adhere to regulations such as GDPR and CCPA. Howeve...

[The supernumerary robotic limbs of brain-computer interface based on asynchronous steady-state visual evoked potential].

Brain-computer interface (BCI) based on steady-state visual evoked potential (SSVEP) have attracted much attention in the field of intelligent robotic...

Opportunities, Risks, Strengths and Weaknesses of Robotic Systems in Early Neurological Rehabilitation.

Given the conference's focus on innovative healthcare solutions, our investigation into robotic assistance systems highlights crucial advancements in ...

Machine Learning with Clinical and Intraoperative Biosignal Data for Predicting Cardiac Surgery-Associated Acute Kidney Injury.

Early identification of patients at high risk of cardiac surgery-associated acute kidney injury (CSA-AKI) is crucial for its prevention. We aimed to l...

Polaris: Open-ended Interactive Robotic Manipulation via Syn2Real Visual Grounding and Large Language Models

This paper investigates the task of the open-ended interactive robotic manipulation on table-top scenarios. While recent Large Language Models (LLMs...

GastroFuse-Net: an ensemble deep learning framework designed for gastrointestinal abnormality detection in endoscopic images.

Convolutional Neural Networks (CNNs) have received substantial attention as a highly effective tool for analyzing medical images, notably in interpret...

Surgical-VQLA++: Adversarial Contrastive Learning for Calibrated Robust Visual Question-Localized Answering in Robotic Surgery

Medical visual question answering (VQA) bridges the gap between visual information and clinical decision-making, enabling doctors to extract underst...

BodySLAM: A Generalized Monocular Visual SLAM Framework for Surgical Applications

Endoscopic surgery relies on two-dimensional views, posing challenges for surgeons in depth perception and instrument manipulation. While Monocular ...

The Literature Review Network: An Explainable Artificial Intelligence for Systematic Literature Reviews, Meta-analyses, and Method Development

Systematic literature reviews are the highest quality of evidence in research. However, the review process is hindered by significant resource and d...

Trends of "Artificial Intelligence, Machine Learning, Virtual Reality, and Radiomics in Urolithiasis" over the Last 30 Years (1994-2023) as Published in the Literature (PubMed): A Comprehensive Review.

To analyze the bibliometric publication trend on the application of "Artificial Intelligence (AI) and its subsets (Machine Learning-ML, Virtual reali...

Artificial Intelligence in Perioperative Care: Opportunities and Challenges.

Artificial intelligence (AI) applications have great potential to enhance perioperative care. This paper explores promising areas for AI in anesthesio...

A Novel Machine-Learning Algorithm to Predict Stone Recurrence with 24-Hour Urine Data.

The absence of predictive markers for kidney stone recurrence poses a challenge for the clinical management of stone disease. The unpredictability of...

Registering Neural 4D Gaussians for Endoscopic Surgery

The recent advance in neural rendering has enabled the ability to reconstruct high-quality 4D scenes using neural networks. Although 4D neural recon...

ASI-Seg: Audio-Driven Surgical Instrument Segmentation with Surgeon Intention Understanding

Surgical instrument segmentation is crucial in surgical scene understanding, thereby facilitating surgical safety. Existing algorithms directly dete...