Surgery

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 acupunctur...

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 a...

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 a...

Optimizing patient monitoring to prevent clinical deterioration in surgical wards using machine learning.

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 imp...

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...

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 ...

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

The prognosis following radical surgery for intrahepatic cholangiocarcinoma (ICC) is poor, and optim...

Making waves: The potential of generative AI in water utility operations.

Water utilities facing increasingly complex infrastructure and operations stand to significantly ben...

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 associa...

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...

Development and evaluation of a machine learning model for post-surgical acute kidney injury in active infective endocarditis.

INTRODUCTION: Acute kidney injury (AKI) is notably prevalent after cardiac surgery for patients with...

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...

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...

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 dee...

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 app...

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 patie...

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 domai...

Artificial intelligence and pediatric surgery: where are we?

Here, we explore the transformative effects of artificial intelligence (AI) and large language model...

Automation of multiplex biochemical assays to enhance productivity and reduce cycle time using a modular robotic platform.

Pharmaceutical and biotechnology companies are increasingly being challenged to shorten the cycle ti...

Computed Tomography Scan and Clinical-based Complete Response Prediction in Locally Advanced Rectal Cancer after Neoadjuvant Chemoradiotherapy: A Machine Learning Approach.

BACKGROUND: Treatment of locally advanced rectal cancer (LARC) involves neoadjuvant chemoradiotherap...