Surgery

The balance between artificial and human intelligence in clinical practice.

INTRODUCTION: Artificial intelligence (AI) is becoming increasingly integrated into clinical care in hand surgery. Its applications extend across diagnosis, planning, intraoperative assistance, postoperative monitoring, rehabilitation, prosthetics and education. APPLICATIONS: In diagnostic imaging, AI improves the detection of distal radius and scaphoid fractures, estimates osteoporosis from hand ...

Deep Learning-Based Detection of Periodontal Infrabony and Furcation Defects on Periapical Radiographs: A Feasibility Study.

INTRODUCTION: Accurate radiographic detection and classification of periodontal osseous defects are essential for prognosis and surgical planning in regenerative periodontology. Traditional diagnostic methods offer limited morphological information, and interpretation can be operator-dependent. Recent advances in artificial intelligence (AI) have shown potential in medical image analysis, but thei...

Machine learning models in predicting viability after testicular torsion: a proof of concept study.

PURPOSE: Decision-making for orchiectomy following testicular torsion often relies on subjective clinical evaluations. This study investigates the eff...

Machine learning in the development and application of patient-reported outcome measures (PROMs) for surgical patients: a systematic review.

BACKGROUND: Artificial intelligence (AI) and machine learning (ML) are increasingly integrated into healthcare, offering potential advancements in pat...

Expectations vs Reality of an Intraoperative Artificial Intelligence Intervention.

IMPORTANCE: Having significant gaps between the expectations and reality of artificial intelligence-based programs can be a major barrier to successfu...

Using Machine Learning to Predict Cochlear Implant Outcomes.

INTRODUCTION: Cochlear implant outcomes vary widely and are difficult to predict, with traditional methods explaining <20% of variance. This study tes...

Risk Factors and Prediction of Chronic Postsurgical Pain Among Patients With Distal Lower Extremity Fracture: Cohort Analysis.

BACKGROUND: The surgical interventions aimed at fracture repair are often accompanied by chronic postsurgical pain (CPSP), which is associated with de...

Approaches to assessing completeness of polyp resections in clinical practice: a systematic scoping review.

BACKGROUND: Protocols for standardized assessment of complete colorectal polyp resection are lacking. This may contribute to divergent quality standar...

Individuation of predictive parameters of posterior cranial fossa decompression in pediatric patients with Chiari I malformation and autism spectrum disorder.

PURPOSE: There are no specific guidelines for posterior cranial fossa decompression (PCFD) in asymptomatic Chiari Malformation Type I (CM-I) patients ...

AI outperforms humans in establishing interpersonal closeness in emotionally engaging interactions, but only when labelled as human.

With the increasing accessibility of large language models to the public, questions arise about whether, and under what conditions, social-emotional i...

Attitudes and readiness of nursing students practising in surgical units towards artificial intelligence: a cross-sectional study.

BACKGROUND: In surgical fields at the forefront of technological advancement with both virtual and physical artificial intelligence applications, nurs...

Machine Learning Predictive Models for Prognosis in Patients undergoing Endovascular Abdominal Aortic Aneurysm Repair.

BACKGROUND: An increasing number of patients with abdominal aortic aneurysms (AAAs) are opting for endovascular aneurysm repair (EVAR), and predicting...

Initial diagnosis and management of acute ischemic stroke: recent update and future direction.

Acute ischemic stroke (AIS) outcomes depend critically on rapid, accurate early diagnosis in the emergency department. Traditional prehospital tools a...

AI of the Beholder: How Surgical and Medical Specialties View Intelligent Technology.

BackgroundHow clinicians conceptualize artificial intelligence reveals underlying assumptions about professional authority and decision-making. This s...

Deep learning feature-based model on abdominal radiography outperforms experts for early necrotizing enterocolitis diagnosis in neonates.

OBJECTIVES: Plain abdominal radiography is a widely used imaging modality for diagnosing neonatal necrotizing enterocolitis (NEC), but the characteris...

From Recognition to Action: Integrating Deep Learning and Robotic Control in Transthoracic Echocardiography.

Population aging has driven a rise in heart failure cases, increasing the clinical burden on cardiac diagnostics. As a first-line imaging method, tran...

Multi-center evaluation of radiomics and deep learning to stratify malignancy risk of IPMNs.

PURPOSE: Distinguishing high-risk intraductal papillary mucinous neoplasms (IPMNs) from low-risk lesions remains a clinical challenge, often resulting...

Non-invasive Prediction of CYP11B2-Defined Subtypes in Primary Aldosteronism Using 18F-Pentixafor PET/CT and Machine Learning.

PURPOSE: This study aims to develop and validate an interpretable machine learning model that integrates clinical data, radiomics, and deep learning (...

Predicting Surgical Outcomes and Optimizing Patients for Surgery Using AI.

Artificial intelligence (AI) platforms and machine learning (ML) algorithms provide the ability to utilize large amounts of electronically available d...

Shap-interpretable predictive modeling of microvascular invasion and early recurrence in hepatocellular carcinoma using MRI habitat imaging combined with clinical features.

OBJECTIVE: To develop and validate an integrated model combining Gd-EOB-DTPA-enhanced MRI habitat imaging with clinical features for preoperative pred...