Surgery

Towards full integration of explainable artificial intelligence in colon capsule endoscopy's pathway.

Despite recent surge of interest in deploying colon capsule endoscopy (CCE) for early diagnosis of colorectal diseases, there remains a large gap between the current state of CCE in clinical practice, and the state of its counterpart optical colonoscopy (OC). This is due to several factors, such as low quality bowel cleansing, logistical challenges around both delivery and collection of the capsul...

Multi-agent deep reinforcement learning-based robotic arm assembly research.

Due to the complexity and variability of application scenarios and the increasing demands for assembly, single-agent algorithms often face challenges in convergence and exhibit poor performance in robotic arm assembly processes. To address these issues, this paper proposes a method that employs a multi-agent reinforcement learning algorithm for the shaft-hole assembly of robotic arms, with a speci...

Application of Artificial Intelligence in Acute Ischemic Stroke: A Scoping Review.

Artificial intelligence (AI) is revolutionizing stroke care by enhancing diagnosis, treatment, and outcome prediction. This review examines 505 origin...

Artificial Intelligence in Commercial Industry: Serving the End-to-End Patient Experience Across the Digital Ecosystem.

The purpose of this article is to evaluate the application of artificial intelligence (AI) from the perspective of the orthopaedic industry with respe...

Label-efficient sequential model-based weakly supervised intracranial hemorrhage segmentation in low-data non-contrast CT imaging.

BACKGROUND: In clinical settings, intracranial hemorrhages (ICH) are routinely diagnosed using non-contrast CT (NCCT) in emergency stroke imaging for ...

Multicenter study on predicting postoperative upper limb muscle strength improvement in cervical spinal cord injury patients using radiomics and deep learning.

Cervical spinal cord injury is often catastrophic, frequently leading to irreversible impairment. MRI has become the gold standard for evaluating spin...

Diagnosis of Benign and Malignant Newly Developed Nodules on the Surgical Side After Breast Cancer Surgery Based on Machine Learning.

To enhance the diagnostic accuracy of new nodules on the surgical side after breast cancer surgery using machine learning techniques and to explore t...

Emergency Position Recovery Using Forward Kinematics in Robotic Patient Positioning Systems for Radiosurgery.

Precise patient positioning is paramount in radiosurgery to ensure the accurate targeting of tumors while minimizing damage to surrounding healthy tis...

A practical deep learning model for core temperature prediction of specialized workers in high-temperature environments.

The health issues of hazardous operations in high-temperature environments are increasing concerns to the public, especially since global warming and ...

Stress hyperglycemia ratio and machine learning model for prediction of all-cause mortality in patients undergoing cardiac surgery.

BACKGROUND: The stress hyperglycemia ratio (SHR) was developed to reduce the effects of long-term chronic glycemic factors on stress hyperglycemia lev...

Artificial intelligence for individualized treatment of persistent atrial fibrillation: a randomized controlled trial.

Although pulmonary vein isolation (PVI) has become the cornerstone ablation procedure for atrial fibrillation (AF), the optimal ablation procedure for...

Perioperative goal-directed therapy with artificial intelligence to reduce the incidence of intraoperative hypotension and renal failure in patients undergoing lung surgery: A pilot study.

STUDY OBJECTIVE: The aim of this study was to investigate whether goal-directed treatment using artificial intelligence, compared to standard care, ca...

Multi-axis robotic forceps with decoupled pneumatic actuation and force sensing for cochlear implantation.

Delicate manual microsurgeries rely on sufficient hands-on experience for safe manipulations. Automated surgical devices can enhance the effectiveness...

Robust multi-label surgical tool classification in noisy endoscopic videos.

Over the past few years, surgical data science has attracted substantial interest from the machine learning (ML) community. Various studies have demon...

Survival machine learning model of T1 colorectal postoperative recurrence after endoscopic resection and surgical operation: a retrospective cohort study.

OBJECTIVE: To construct a postoperative recurrence prediction model for patients with T1 colorectal cancer after endoscopic resection and surgical ope...

Preoperatively predicting failure to achieve the minimum clinically important difference and the substantial clinical benefit in patient-reported outcome measures for total hip arthroplasty patients using machine learning.

BACKGROUND: Attention to the collection of patient-reported outcomes measures (PROMs) associated with total hip arthroplasty (THA) is growing. The aim...

A novel trajectory learning method for robotic arms based on Gaussian Mixture Model and k-value selection algorithm.

In the field of robotic arm trajectory imitation learning, Gaussian Mixture Models are widely used for their ability to capture the characteristics of...

Functional MRI-based machine learning strategy for prediction of postoperative delirium in cardiac surgery patients: A secondary analysis of a prospective observational study.

STUDY OBJECTIVE: Delirium is a common complication after cardiac surgery and is associated with poor prognosis. An effective delirium prediction model...

Machine Learning Approach to Identifying Wrong-Site Surgeries Using Centers for Medicare and Medicaid Services Dataset: Development and Validation Study.

BACKGROUND: Wrong-site surgery (WSS) is a critical but preventable medical error, often resulting in severe patient harm and substantial financial cos...

Diagnosis and treatment of a rare bilateral primary thyroid cancer: a case report.

Preoperative ultrasound examination of thyroid nodules is the most economical and effective screening method for diagnosing thyroid nodules. Fine-need...