Surgery

Enhancing wrist arthroscopy: artificial intelligence applications for bone structure recognition using machine learning.

INTRODUCTION: Wrist arthroscopy is a rapidly expanding surgical discipline, but has a long and challenging learning curve. One of its difficulties is distinguishing the various anatomical structures during the procedure. Although artificial intelligence has made significant progress in recent decades, its potential as a valuable tool in surgery training is largely untapped.

Predicting post-surgical functional status in high-grade glioma with resting state fMRI and machine learning.

PURPOSE: High-grade glioma (HGG) is the most common and deadly malignant glioma of the central nervous system. The current standard of care includes surgical resection of the tumor, which can lead to functional and cognitive deficits. The aim of this study is to develop models capable of predicting functional outcomes in HGG patients before surgery, facilitating improved disease management and inf...

Improved differentiation of cavernous malformation and acute intraparenchymal hemorrhage on CT using an AI algorithm.

This study aimed to evaluate the utility of an artificial intelligence (AI) algorithm in differentiating between cerebral cavernous malformation (CCM)...

Testing Dynamic Balance in People with Multiple Sclerosis: A Correlational Study between Standard Posturography and Robotic-Assistive Device.

BACKGROUND: Robotic devices are known to provide pivotal parameters to assess motor functions in Multiple Sclerosis (MS) as dynamic balance. However, ...

Mitigating Trunk Compensatory Movements in Post-Stroke Survivors through Visual Feedback during Robotic-Assisted Arm Reaching Exercises.

Trunk compensatory movements frequently manifest during robotic-assisted arm reaching exercises for upper limb rehabilitation following a stroke, pote...

Risk assessment of organ transplant operation: A fuzzy hybrid MCDM approach based on fuzzy FMEA.

Nowadays, most fatal diseases are attributed to the malfunction of bodily. Sometimes organ transplantation is the only possible therapy, for instance ...

Turn Your Vision into Reality-AI-Powered Pre-operative Outcome Simulation in Rhinoplasty Surgery.

BACKGROUND: The increasing demand and changing trends in rhinoplasty surgery emphasize the need for effective doctor-patient communication, for which ...

Pre-operative lung ablation prediction using deep learning.

OBJECTIVE: Microwave lung ablation (MWA) is a minimally invasive and inexpensive alternative cancer treatment for patients who are not candidates for ...

Deep learning ensembles for detecting brain metastases in longitudinal multi-modal MRI studies.

Metastatic brain cancer is a condition characterized by the migration of cancer cells to the brain from extracranial sites. Notably, metastatic brain ...

A new machine learning model to predict the prognosis of cardiogenic brain infarction.

Cardiogenic cerebral infarction (CCI) is a disease in which the blood supply to the blood vessels in the brain is insufficient due to atherosclerosis ...

Machine learning-based preoperative analytics for the prediction of anastomotic leakage in colorectal surgery: a swiss pilot study.

BACKGROUND: Anastomotic leakage (AL), a severe complication following colorectal surgery, arises from defects at the anastomosis site. This study eval...

Machine learning models for predicting early hemorrhage progression in traumatic brain injury.

This study explores the progression of intracerebral hemorrhage (ICH) in patients with mild to moderate traumatic brain injury (TBI). It aims to predi...

Hyperspectral imaging with machine learning for in vivo skin carcinoma margin assessment: a preliminary study.

Surgical excision is the most effective treatment of skin carcinomas (basal cell carcinoma or squamous cell carcinoma). Preoperative assessment of tum...

Prediction of Cochlear Implant Fitting by Machine Learning Techniques.

OBJECTIVE: This study aimed to evaluate the differences in electrically evoked compound action potential (ECAP) thresholds and postoperative mapping c...

Machine learning models on a web application to predict short-term postoperative outcomes following anterior cervical discectomy and fusion.

BACKGROUND: The frequency of anterior cervical discectomy and fusion (ACDF) has increased up to 400% since 2011, underscoring the need to preoperative...

Intraoperative left-sided colorectal anastomotic testing in clinical practice: a multi-treatment machine-learning analysis of the iCral3 prospective cohort.

BACKGROUND: Current evidence about intraoperative anastomotic testing after left-sided colorectal resections is still controversial. The aim of this s...

Personalized prediction of postoperative complication and survival among Colorectal Liver Metastases Patients Receiving Simultaneous Resection using machine learning approaches: A multi-center study.

BACKGROUND: To predict clinical important outcomes for colorectal liver metastases (CRLM) patients receiving colorectal resection with simultaneous li...

Points of interest linear attention network for real-time non-rigid liver volume to surface registration.

BACKGROUND: In laparoscopic liver surgery, accurately predicting the displacement of key intrahepatic anatomical structures is crucial for informing t...

Real-time detection of active bleeding in laparoscopic colectomy using artificial intelligence.

BACKGROUND: Most intraoperative adverse events (iAEs) result from surgeons' errors, and bleeding is the majority of iAEs. Recognizing active bleeding ...

The Surgical Clerkship in the COVID Era: A Natural Language Processing and Thematic Analysis.

INTRODUCTION: Responses to COVID-19 within medical education prompted significant changes to the surgical clerkship. We analyzed the changes in medica...