Surgery

Using Masked Image Modelling Transformer Architecture for Laparoscopic Surgical Tool Classification and Localization.

Artificial intelligence (AI) has shown its potential to advance applications in various medical fields. One such area involves developing integrated AI-based systems to assist in laparoscopic surgery. Surgical tool detection and phase recognition are key components to develop such systems, and therefore, they have been extensively studied in recent years. Despite significant advancements in this f...

Analysis of Single Nuclei in a Microfluidic Cytometer Towards Metaphase Enrichment.

Identifying analyzable metaphase chromosomes is crucial for karyotyping, a common procedure used by clinicians to diagnose genetic disorders and some forms of cancer. This task is often laborious and time-consuming, making it essential to develop automated, efficient, and reliable methods to assist clinical technicians. In this work, an original label-free microfluidic approach to identify potenti...

Role of Neck Pain in Defining Clinical Trajectories of Outcomes in Patients With Degenerative Cervical Myelopathy: Results of a Novel Machine Learning Algorithm.

Study DesignRetrospective analysis of prospective data.ObjectivesNeck pain represents a crucial factor underscoring a patient's decision to receive su...

Preoperative radiomics models using CT and MRI for microsatellite instability in colorectal cancer: a systematic review and meta-analysis.

OBJECTIVE: Microsatellite instability (MSI) is a novel predictive biomarker for chemotherapy and immunotherapy response, as well as prognostic indicat...

Machine learning model to predict sepsis in ICU patients with intracerebral hemorrhage.

Patients with intracerebral hemorrhage (ICH) are highly susceptible to sepsis. This study evaluates the efficacy of machine learning (ML) models in pr...

Risk factors and predictive models for post-operative moderate-to-severe mitral regurgitation following transcatheter aortic valve replacement: a machine learning approach.

BACKGROUND: Post-operative moderate-to-severe mitral regurgitation (MR) following transcatheter aortic valve replacement (TAVR) is associated with poo...

Integration of sentinel node mapping and molecular classification in endometrial cancer staging.

Sentinel node mapping has gained popularity in surgical staging of endometrial cancer, providing a less invasive alternative to lymphadenectomy for st...

Investigating perioperative pressure injuries and factors influencing them with imbalanced samples using a Synthetic Minority Over-sampling Technique.

This study investigates the use of machine learning (ML) models combined with a Synthetic Minority Over-sampling Technique (SMOTE) and its variants to...

Development of a prognostic model for osteosarcoma based on macrophage polarization-related genes using machine learning: implications for personalized therapy.

While neoadjuvant chemotherapy combined with surgical resection has improved the prognosis for patients with osteosarcoma, its impact on metastatic an...

Machine learning-based prediction of 90-day prognosis and in-hospital mortality in hemorrhagic stroke patients.

This study aims to predict hemorrhagic stroke outcomes, including 90-day prognosis and in-hospital mortality, using machine learning models and SHaple...

Noninvasive blood glucose monitoring using a dual band microwave sensor with machine learning.

The potential for continuous non-invasive blood glucose monitoring has attracted a lot of interest in the field of medical diagnostics. This paper pro...

Thirty-day mortality risk prediction for geriatric patients undergoing non-cardiac surgery in the surgical intensive care unit.

BACKGROUND: The prediction of mortality for elderly patients undergoing non-cardiac surgeries is a vital research area, as accurate risk assessment ca...

Editorial Commentary: Deteriorated Quality and Medial Retraction of Tendon Following Acute Traumatic Rotator Cuff Tear Are Predictors of Retear After Arthroscopic Repair.

Rotator cuff tears are a common cause of shoulder pain and dysfunction, affecting up to 33% of the population, and approximately 250,000 arthroscopic ...

CottonSim: Development of an autonomous visual-guided robotic cotton-picking system in the Gazebo

In this study, an autonomous visual-guided robotic cotton-picking system, built on a Clearpath's Husky robot platform and the Cotton-Eye perception ...

Artificial Intelligence in Glaucoma: Advances in Diagnosis, Progression Forecasting, and Surgical Outcome Prediction.

Glaucoma is a leading cause of irreversible blindness, with challenges persisting in early diagnosis, disease progression, and surgical outcome predic...

Hierarchical diagnosis of breast phyllodes tumors enabled by deep learning of ultrasound images: a retrospective multi-center study.

OBJECTIVE: Phyllodes tumors (PTs) are rare breast tumors with high recurrence rates, current methods relying on post-resection pathology often delay d...

Development and Validation of Machine Learning Algorithms for Predicting Prolonged Postoperative Opioid Use in Spinal Metastatic Disease.

Introduction: Operative management of spinal metastatic disease is largely for symptom palliation and revolves around the expectation that postoperati...

Deep Learning-Based Retinoblastoma Protein Subtyping of Pulmonary Large-Cell Neuroendocrine Carcinoma on Small Hematoxylin and Eosin-Stained Specimens.

Molecular subtyping of pulmonary large-cell neuroendocrine carcinoma (LCNEC) based on retinoblastoma protein (pRb) expression may influence systemic t...

Precision, intelligence, and a new paradigm for chemical research.

Chemists have long struggled to precisely regulate and create substances, often relying on trial-and-error methods that are inefficient for complex, h...

Automated Action Generation based on Action Field for Robotic Garment Manipulation

Garment manipulation using robotic systems is a challenging task due to the diverse shapes and deformable nature of fabric. In this paper, we propos...