Surgery

Discrimination of Dengue Diseases in Children Using Surface-Enhanced Raman Spectroscopy Coupled with Machine Learning Approaches.

This study introduces a novel approach to dengue diagnostics by leveraging surface-enhanced Raman spectroscopy (SERS) coupled to machine learning. This method addresses the critical need for rapid and accurate identification of dengue virus (DENV) infection and prediction of the disease severity. For the first time, a commercialized SERS substrate is applied to analyze plasma samples from 60 pedia...

A comparative study of machine learning models predicting post-hepatectomy liver failure: enhancing risk estimation in over 25,000 National Surgical Quality Improvement Program patients.

BACKGROUNDS/AIMS: Post-hepatectomy liver failure (PHLF) is a significant complication with an incidence rate between 8% and 12%. Machine learning (ML) can analyze large datasets to uncover patterns not apparent through traditional methods, enhancing PHLF prediction and potentially mitigate complications.

AI-assisted prostheses manufacturing for cranioplasties in low-income countries. A case report and technique description.

Cranioplasty restores skull integrity after decompressive craniectomy, but high costs limit access in low-resource settings. This case highlights an a...

Predictive modeling and machine learning show poor performance of clinical, morphological, and hemodynamic parameters for small intracranial aneurysm rupture.

Small intracranial aneurysms (SIAs) (< 5 mm) are increasingly detected due to advanced imaging, but predicting rupture risk remains challenging. Ruptu...

Wristful thinking: exploring the effects of robotic rehabilitation and cross-education for persons with multiple sclerosis.

The goal of this work was to develop an adaptive rehabilitation technique using a haptic wrist robot that would induce cross-education to an untrained...

Robot-Assisted Retrograde Intrarenal Surgery: A Mini Review of the Literature on Robotic Surgery Platforms for Endoscopic Stone Surgery.

Retrograde intrarenal surgery (RIRS) has become a cornerstone in renal stone management, with robotic platforms recently entering clinical practice. T...

Ultrasound Imaging and Machine Learning to Detect Missing Hand Motions for Individuals Receiving Targeted Muscle Reinnervation for Nerve-Pain Prevention.

Targeted muscle reinnervation (TMR) was initially developed as a technique for bionic prosthetic control but has since become a widely adopted strateg...

A self-supervised robotic system for autonomous contact-based spatial mapping of semiconductor properties.

Integrating robotically driven contact-based material characterization techniques into self-driving laboratories can enhance measurement quality, reli...

Identifying features of prior hemorrhage in cerebral cavernous malformations on quantitative susceptibility maps: a machine learning pilot study.

Features of new bleeding on conventional imaging in cerebral cavernous malformations (CCMs) often disappear after several weeks, yet the risk of reble...

Accuracy and Reliability of ChatGPT in Answering Patient Questions About Lung Cancer and Its Surgery: An Expert Panel Evaluation by Thoracic Surgeons.

This study aimed to evaluate the accuracy, clarity, and scientific adequacy of ChatGPT's responses to frequently asked patient questions concerning lu...

Prediction of postoperative infection through early-stage salivary microbiota following kidney transplantation using machine learning techniques.

Kidney transplantation (KT) is an effective treatment for end-stage renal disease; however, the lifelong immunosuppressive regimen increases the risk ...

Can Whole-Thyroid-Based CT Radiomics Model Achieve the Performance of Lesion-Based Model in Predicting the Thyroid Nodules Malignancy? - A Comparative Study.

Machine learning is now extensively implemented in medical imaging for preoperative risk stratification and post-therapeutic outcome assessment, enhan...

Artificial intelligence for electrocardiographic diagnosis of perioperative myocardial ischaemia: a scoping review.

BACKGROUND: Perioperative electrocardiographic monitoring can offer immediate detection of myocardial ischaemia, yet its application in perioperative ...

Imaging Based Surgical Site Infection Detection Using Artificial Intelligence.

OBJECTIVE: To develop an AI-based pipeline to assess and triage patient-submitted postoperative wound images.

Machine learning algorithms for prediction of cerebrospinal fluid leakage after posterior surgery for thoracic ossification of the ligamentum flavum.

To develop and validate a machine-learning (ML) model that pre-operatively predicts cerebrospinal-fluid leakage (CSFL) after posterior decompression f...

Surgical skill assessment using an AI-based surgical phase recognition model for laparoscopic cholecystectomy.

BACKGROUND: Automated surgical skill assessment using artificial intelligence (AI) in laparoscopic cholecystectomy (Lap-C) can be a valuable method fo...

Artificial Intelligence-Assisted Conductive Hydrogel Dressings for Refractory Wounds Monitoring.

Refractory wounds cause significant harm to the health of patients and the most common treatments in clinical practice are surgical debridement and wo...

Individualized structural network deviations predict surgical outcome in mesial temporal lobe epilepsy: a multicentre validation study.

BACKGROUND: Surgical resection is an effective treatment for medically refractory mesial temporal lobe epilepsy (mTLE), however, more than one-third o...

In Vivo Laparoscopic Image De-smoking Dataset, Evaluation, and Beyond.

The development of effective algorithms for removing surgical smoke in laparoscopic surgery has been hindered by the absence of a paired dataset conta...

Multimodal nomogram integrating deep learning radiomics and hemodynamic parameters for early prediction of post-craniotomy intracranial hypertension.

To evaluate the effectiveness of deep learning radiomics nomogram in distinguishing early intracranial hypertension (IH) following primary decompressi...