Surgery

Imaging-guided bioresorbable acoustic hydrogel microrobots.

Micro- and nanorobots excel in navigating the intricate and often inaccessible areas of the human body, offering immense potential for applications such as disease diagnosis, precision drug delivery, detoxification, and minimally invasive surgery. Despite their promise, practical deployment faces hurdles, including achieving stable propulsion in complex in vivo biological environments, real-time i...

Acupuncture and moxibustion as adjunctive therapy for postoperative gastrointestinal dysfunction in gastric cancer: a systematic review and network meta-analysis.

OBJECTIVES: This study aimed to evaluate and compare the efficacy and safety of different acupuncture and moxibustion techniques as adjunctive therapy in addressing Postoperative gastrointestinal dysfunction (PGD) associated with gastric cancer (GC).

Editorial: The evolution of minimally invasive urologic surgery: innovations, challenges, and opportunities.

Development and validation of interpretable machine learning models for postoperative pneumonia prediction.

BACKGROUND: Postoperative pneumonia, a prevalent form of hospital-acquired pneumonia, poses significant risks to patients' prognosis and even their li...

Utilizing deep learning-based causal inference to explore vancomycin's impact on continuous kidney replacement therapy necessity in blood culture-positive intensive care unit patients.

Patients with positive blood cultures in the intensive care unit (ICU) are at high risk for septic acute kidney injury requiring continuous kidney rep...

Machine Learning-Based Prediction for In-Hospital Mortality After Acute Intracerebral Hemorrhage Using Real-World Clinical and Image Data.

BACKGROUND: Machine learning (ML) techniques are widely employed across various domains to achieve accurate predictions. This study assessed the effec...

Super-fast and accurate nonlinear foot deformation Prediction using graph neural networks.

Recently, there has been a significant increase in the number of foot diseases, highlighting the importance of non-surgical treatments. Customized ins...

Classification of speech arrests and speech impairments during awake craniotomy: a multi-databases analysis.

PURPOSE: Awake craniotomy presents a unique opportunity to map and preserve critical brain functions, particularly speech, during tumor resection. The...

Wound imaging software and digital platform to assist review of surgical wounds using patient smartphones: The development and evaluation of artificial intelligence (WISDOM AI study).

INTRODUCTION: Surgical patients frequently experience post-operative complications at home. Digital remote monitoring of surgical wounds via image-bas...

Machine learning-based prognostic prediction and surgical guidance for intrahepatic cholangiocarcinoma.

The prognosis following radical surgery for intrahepatic cholangiocarcinoma (ICC) is poor, and optimal follow-up strategies remain unclear, with ongoi...

Prediction of Symptomatic Intracranial Hemorrhage Before Mechanical Thrombectomy Using Machine Learning in Patients with Anterior Circulation Large Vessel Occlusion.

BACKGROUND: Symptomatic intracranial hemorrhage (sICH) after mechanical thrombectomy (MT) is associated with worse outcomes. We sought to develop and ...

Machine learning for predicting poor outcomes in aneurysmal subarachnoid hemorrhage: A systematic review and meta-analysis involving 8445 participants.

Early prediction of poor outcomes in patients impacted with aneurysmal subarachnoid hemorrhage (aSAH) is crucial for timely intervention and effective...

Development and validation of a deep learning algorithm for the classification of the level of surgical difficulty in impacted mandibular third molar surgery.

The aim of this study was to develop and validate a convolutional neural network (CNN) algorithm for the detection of impacted mandibular third molars...

Deep learning-driven multi-omics sequential diagnosis with Hybrid-OmniSeq: Unraveling breast cancer complexity.

BackgroundBreast cancer results from an uncontrolled growth of breast tissue. Many methods of diagnosis are using multi-omics data to better understan...

Deep learning-based overall survival prediction in patients with glioblastoma: An automatic end-to-end workflow using pre-resection basic structural multiparametric MRIs.

PURPOSE: Accurate and automated early survival prediction is critical for patients with glioblastoma (GBM) as their poor prognosis requires timely tre...

Prediction of Brain Cancer Occurrence and Risk Assessment of Brain Hemorrhage Using Hybrid Deep Learning Technique.

The prediction of brain cancer occurrence and risk assessment of brain hemorrhage using a hybrid deep learning (DL) technique is a critical area of re...

Self-Supervised Cyclic Diffeomorphic Mapping for Soft Tissue Deformation Recovery in Robotic Surgery Scenes.

The ability to recover tissue deformation from surgical video is fundamental for many downstream applications in robotic surgery. Despite noticeable a...

Single-Port Three-Dimensional Endoscopic-Assisted Axillary Lymph Node Dissection (S-P 3D E-ALND): Surgical Technique and Preliminary Results.

Endoscopic-assisted breast surgery (EABS) provides better cosmetic outcomes for breast cancer patients with small incisions in an inconspicuous area....

Artificial intelligence and pediatric surgery: where are we?

Here, we explore the transformative effects of artificial intelligence (AI) and large language models (LLMs), such as ChatGPT and GEMINI, on pediatric...

The use of cloud based machine learning to predict outcome in intracerebral haemorrhage without explicit programming expertise.

Machine Learning (ML) techniques require novel computer programming skills along with clinical domain knowledge to produce a useful model. We demonstr...