Surgery

Artificial Intelligence and its Applications in Orthodontics and Dentofacial Orthopedics.

In this article, the authors review the potential influence and benefits of artificial intelligence (AI) in orthodontics and dentofacial orthopedics with particular emphasis on current applications and emerging developments. Specific focus areas such as diagnosis, growth evaluation, treatment planning, personalized care, robotic technologies, virtual surgical planning, and improvements in clinical...

Machine Learning Predictions for Assessing Hard-to-Place Deceased Donor Kidneys.

RATIONALE & OBJECTIVE: Nearly 20% of deceased donor kidneys in the United States are placed "out-of-sequence" (ie, outside of standard allocation rules). The rationale for out-of-sequence placements is to expedite placement of kidneys at risk of nonuse. We aimed to (1) develop machine learning (ML) models to predict the risk of kidney nonuse over time during the allocation process and (2) use the ...

Head-to-Head Comparison of 2 Artificial Intelligence Computer-Aided Triage Solutions for Detecting Intracranial Hemorrhage on Noncontrast Head CT.

BACKGROUND AND PURPOSE: This study aims to provide a comprehensive comparison of the performance and reproducibility of 2 commercially available artif...

Comparison of the predictive performance of machine learning and conventional logistic regression models for poor discharge outcomes in patients with Aneurysmal subarachnoid hemorrhage: A retrospective cohort study.

AI Tools in Plastic Surgery: A Scoping Review.

BACKGROUND: The use and standardization of innovative artificial intelligence (AI) tools continue to grow and have the potential to enhance the field ...

Computer-Guided Biopsy of Osteosclerotic Jaw Lesion Using 3D-Printed Surgical Guides: A Fully Digital Workflow.

Osteosclerotic jaw lesions, often incidentally detected on routine radiographs, are rarely biopsied due to their benign appearance and proximity to de...

[Artificial intelligence in surgical disciplines: Clinical application, advantages, and potential-a Delphi expert consensus].

BACKGROUND: Artificial intelligence (AI) in surgical disciplines has the potential to support all areas of patient care, with the goal of improving tr...

An interpretable machine learning model for predicting survival in pancreatic cancer via SHAP: a multicenter study.

BACKGROUND: Existing pancreatic cancer prediction models still have significant limitations until now. This multicenter retrospective study aimed to i...

Artificial intelligence versus classical scoring systems: a comparative analysis of stone-free prediction after percutaneous nephrolithotomy.

This study aimed to compare the predictive performance of traditional stone scoring systems with a large language model based on ChatGPT in estimating...

Deep Learning and Noninvasive Sensors for Detecting Physiological Dysregulation: A Scoping Review.

Early detection of pain, stress, or hemodynamic instability is key to preventing serious clinical events. In recent years, non-invasive sensors and de...

Predictive Performance of Artificial Intelligence Algorithms for Gestational Diabetes Mellitus in Pregnant Women: Systematic Review and Meta-Analysis.

BACKGROUND: Gestational diabetes mellitus (GDM) is a common complication during pregnancy, with its incidence increasing year by year. It poses numero...

Machine Learning Algorithms to Predict Venous Thromboembolism in Patients With Sepsis in the Intensive Care Unit: Multicenter Retrospective Study.

BACKGROUND: Venous thromboembolism (VTE) is a common and severe complication in intensive care unit (ICU) patients with sepsis. Conventional risk stra...

Predicting transcranial ultrasound insertion loss using skull CT: A deep learning approach.

Transcranial ultrasound (tUS) is a non-invasive neuromodulation technique with applications in brain disorders. However, ultrasound attenuation induce...

Autorep: Automatic network search with structured reparameterized based linear operation expansion and gradient proxy guided reduction.

Convolution neural network and Vision Transformer have achieved large success in various computer vision tasks. However, the huge computation cost hin...

Minimally Invasive / Robotic Surgery for Hepatobiliary Cancer.

Minimally invasive liver surgery (MILS), including laparoscopic liver surgery and robotic liver surgery, has come a long way in the management of prim...

ESM-AnatTractNet: Advanced deep learning model of true positive eloquent white matter tractography to improve preoperative evaluation of pediatric epilepsy surgery.

Accurate preoperative identification of true positive white matter pathways involved in critical eloquent functions such as motor, language, and visio...

Comparison of the accuracy of Robotic arm and Dynamic Navigation in the placement of mandibular dental implants: An in-vitro study.

OBJECTIVE: To compare the spatial accuracy between Robotic Computer-Assisted implant Surgery (R-CAIS) and Dynamic Computer-Assisted Implant Surgery (D...

Evaluating the methodological suitability of partial dependence plots and Shapley additive explanations for population-level interpretation of machine learning models in total joint arthroplasty.

BACKGROUND: Total joint arthroplasty (TJA) complications necessitate the development of accurate risk prediction models; however, interpretability in ...

Use of Electrocardiograms to Identify Coronary Artery Disease: Cross-Validation of an Artificial Intelligence Model.

BACKGROUND: The current gold standard for the diagnosis of coronary artery disease (CAD) is invasive angiography; however, it is an invasive procedure...

Evaluating Plastic Surgery Chatbot Performance: Insights into Medical Triage, Classification Accuracy, and Escalation Trends.

BACKGROUND: The integration of AI chatbots into plastic surgery websites is now standard, providing asynchronous, real-time engagement for patients. A...