Surgery

A Robotic Clamped-Kinematic System to Study Knee Ligament Injury.

Knee ligament injury is among the most common sports injuries and is associated with long recovery periods and low return-to-sport rates. Unfortunately, the mechanics of ligament injury are difficult to study in vivo, and computational studies provide limited insight. The objective of this study was to implement and validate a robotic system capable of reproducing natural six degree-of-freedom cla...

Role of artificial intelligence in treatment planning and outcome prediction of jaw corrective surgeries by using 3-D imaging: a systematic review.

OBJECTIVE: Artificial intelligence (AI) has been increasingly utilized in diagnosis of skeletal deformities, while its role in treatment planning and outcome prediction of jaw corrective surgeries with 3-dimensional (3D) imaging remains underexplored.

Preoperative markers for identifying CT ≤2 cm solid nodules of lung adenocarcinoma based on image deep learning.

BACKGROUND: The solid pattern is a highly malignant subtype of lung adenocarcinoma. In the current era of transitioning from lobectomy to sublobar res...

PViT-AIR: Puzzling vision transformer-based affine image registration for multi histopathology and faxitron images of breast tissue.

Breast cancer is a significant global public health concern, with various treatment options available based on tumor characteristics. Pathological exa...

Development and validation of a robotic system for milling individualized jawbone cavities in oral and maxillofacial surgery.

OBJECTIVES: This study aimed to develop and validate a robotic system capable of performing accurate and minimally invasive jawbone milling procedures...

Machine-learning-based models for the optimization of post-cervical spinal laminoplasty outpatient follow-up schedules.

BACKGROUND: Patients undergo regular clinical follow-up after laminoplasty for cervical myelopathy. However, those whose symptoms significantly improv...

Predicting Intra- and Postpartum Hemorrhage through Artificial Intelligence.

: Intra/postpartum hemorrhage stands as a significant obstetric emergency, ranking among the top five leading causes of maternal mortality. The aim of...

Machine-learning based prediction model for acute kidney injury induced by multiple wasp stings.

Acute kidney injury (AKI) following multiple wasp stings is a severe complication with potentially poor outcomes. Despite extensive research on AKI's ...

Real-time segmentation of biliary structure in pure laparoscopic donor hepatectomy.

Pure laparoscopic donor hepatectomy (PLDH) has become a standard practice for living donor liver transplantation in expert centers. Accurate understan...

Combining 2.5D deep learning and conventional features in a joint model for the early detection of sICH expansion.

The study aims to investigate the potential of training efficient deep learning models by using 2.5D (2.5-Dimension) masks of sICH. Furthermore, it in...

A machine learning-based Coagulation Risk Index predicts acute traumatic coagulopathy in bleeding trauma patients.

BACKGROUND: Acute traumatic coagulopathy (ATC) is a well-described phenomenon known to begin shortly after injury. This has profound implications for ...

Impact of a deep learning-based brain CT interpretation algorithm on clinical decision-making for intracranial hemorrhage in the emergency department.

Intracranial hemorrhage is a critical emergency that requires prompt and accurate diagnosis in the emergency department (ED). Deep learning technology...

Developing machine learning models for personalized treatment strategies in early breast cancer patients undergoing neoadjuvant systemic therapy based on SEER database.

This study aimed to compare the long-term outcomes of breast-conserving surgery plus radiotherapy (BCS + RT) and mastectomy in early breast cancer (EB...

Predictive modeling of arginine vasopressin deficiency after transsphenoidal pituitary adenoma resection by using multiple machine learning algorithms.

This study aimed to predict arginine vasopressin deficiency (AVP-D) following transsphenoidal pituitary adenoma surgery using machine learning algorit...

Transfer learning-enabled outcome prediction for guiding CRRT treatment of the pediatric patients with sepsis.

Continuous renal replacement therapy (CRRT) is a life-saving procedure for sepsis but the benefit of CRRT varies and prediction of clinical outcomes i...

Restoring of Interhemispheric Symmetry in Patients With Stroke Following Bilateral or Unilateral Robot-Assisted Upper-Limb Rehabilitation: A Pilot Randomized Controlled Trial.

Bilateral robotic rehabilitation has proven helpful in the recovery of upper limb motor function in patients with stroke, but its effects on the corti...

An Artificial Intelligence Algorithm Integrated into the Clinical Workflow Can Ensure High Quality Acute Intracranial Hemorrhage CT Diagnostic.

PURPOSE: Intracranial hemorrhage (ICH) is a life-threatening condition requiring rapid diagnostic and therapeutic action. This study evaluates whether...

Efficacy of a whole slide image-based prediction model for lymph node metastasis in T1 colorectal cancer: A systematic review.

BACKGROUND AND AIM: Accurate stratification of the risk of lymph node metastasis (LNM) following endoscopic resection of submucosal invasive (T1) colo...

Multifunctional Human-Computer Interaction System Based on Deep Learning-Assisted Strain Sensing Array.

Continuous and reliable monitoring of gait is crucial for health monitoring, such as postoperative recovery of bone joint surgery and early diagnosis ...

Development and Internal Validation of Machine Learning to Predict Postoperative Worse Functional Status after Surgical Treatment for Thoracic Spinal Stenosis.

BACKGROUND The objective of this study was to develop and validate machine learning (ML) algorithms to predict the 30-day and 6-month risk of deterior...