Anesthesiology

AI-assisted preoperative planning combined with robotic-assisted total knee arthroplasty vs. conventional surgery: a retrospective controlled study.

OBJECTIVE: To compare perioperative outcomes and early functional recovery between AI-robotic and conventional total knee arthroplasty (TKA). METHODS: We retrospectively analyzed data from 88 patients who underwent primary unilateral TKA for knee osteoarthritis between April 2024 and December 2024. The AI-robotic group (n = 44) received AI-assisted preoperative planning and robot-assisted TKA, whi...

Day surgery mode of multi-modal image AI fusion targeted transperineal biopsy technique using electromagnetic navigation tracking system under local anesthesia.

Artificial Intelligence Monitoring of Neurological Status From Patient Videos in the Neuroscience Intensive Care Unit.

BACKGROUND AND OBJECTIVES: The neurological examination is pivotal in assessing patients with neurological conditions but has severe limitations: It c...

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...

Current treatment options for perinatal depression.

PURPOSE OF REVIEW: Perinatal depression (PND) affects up to one in five patients and is the leading cause of maternal mortality, yet remains underdiag...

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...

Risk Factors and an Interpretable Machine Learning Model for Predicting Spinal Epidural Lipomatosis: A Multicenter Study.

STUDY DESIGN: A retrospective multicenter study. OBJECTIVE: To identify independent risk factors for spinal epidural lipomatosis (SEL) and to develop ...

Artificial Intelligence and Its Role in Endoscopic Adenoma and Cancer Detection.

Colorectal cancer incidence and mortality have declined over time, due in part to high-quality screening and surveillance colonoscopy. Nevertheless, p...

[When everything is well-coordinated in an interdisciplinary manner-Is there a need for operating room management?].

Even in the ideal case of well-coordinated cooperation between anesthesiological and surgical as well as interventional colleagues, a departmental con...

The Role of Perioperative Artificial Intelligence in Colon and Rectal Surgery.

Artificial intelligence (AI) is rapidly transforming surgical practice with growing applications in colon and rectal surgery. This review explores per...

Radiologist- and computer-based chest imaging quantification at 12 months post transplant correlates with baseline lung allograft dysfunction.

BACKGROUND: Baseline lung allograft dysfunction (BLAD), defined as failure to achieve ≥ 80% predicted spirometry after lung transplant, is associated ...

Artificial Intelligence-Driven Decision-Making for Knee Joint Manipulation Following Primary Total Knee Arthroplasty.

BACKGROUND: Manipulation under anesthesia (MUA) is a commonly performed procedure to address postoperative stiffness after total knee arthroplasty (TK...

Performance of ChatGPT versus spine surgeons as an emergency department spine call consultant.

BACKGROUND: Large language models (LLMs) like ChatGPT are increasingly being recognized as credible tools for use across diverse healthcare settings. ...

[Expert consensus on neurosurgical robot-assisted deep brain stimulation surgery (2026 edition)].

Robot-assisted deep brain stimulation (DBS) surgical systems in neurosurgery have demonstrated significant advantages in enhancing operative precision...

Development and Validation of an Interpretable Machine Learning Model for Predicting Early Fusion After Anterior Cervical Discectomy and Fusion.

STUDY DESIGN: Retrospective case-control study. OBJECTIVES: This study aimed to develop and preliminarily validate a machine learning (ML) model for p...

Integrative metabolomics and machine learning reveal diagnostic biomarkers for gelsenicine intoxication.

ETHNOPHARMACOLOGICAL RELEVANCE: Gelsemium elegans Benth. (G. elegans) is a highly toxic medicinal plant traditionally used to treat pain and inflammat...

Persistent dysmorphology and dysfunction of the brain microvasculature following repeated trauma.

Mild traumatic brain injury typically produces no abnormalities on neuroimaging yet elicits symptoms that, in an increasing fraction of survivors, lin...

Artificial intelligence in cardiothoracic monitoring and echocardiography.

PURPOSE OF REVIEW: This review describes the recent advancements of artificial intelligence (AI) in cardiothoracic anesthesia monitoring. RECENT FINDI...

Machine Learning-Based Prediction of Postoperative Vasoplegia After Cardiac Surgery.

OBJECTIVE: To develop and internally validate a machine-learning model for the early prediction of postoperative vasoplegia after cardiac surgery. DES...

Learning curve for fenestrated-branched endovascular aortic repair using machine learning: A prospective national multicenter registry study.

OBJECTIVE: Fenestrated-branched endovascular aortic repair (F-BEVAR) is a complex procedure that requires significant experience and advanced technica...