Surgery

Artificial intelligence and surgical innovation: lower limb arthroplasty.

The number of patients requiring hip and knee arthroplasty continues to rise each year. Patients are living longer and expecting to remain active into later life following joint replacement. Developments in computer-assisted surgery and robotic technology may optimise surgical outcomes and patient satisfaction following lower limb arthroplasty. The use of artificial intelligence in healthcare is r...

Ovoid Foramen Magnum Shape is Associated with Increased Complications and Decreased Extent of Resection for Anterolateral Foramen Magnum Meningiomas.

 Antero-laterally located meningiomas of the foramen magnum (FM) pose significant surgical resection challenges. The effect of FM shape on surgical resection of FM meningiomas has not been previously studied. The present study investigates how FM shape effects the extent of tumor resection and complication rates in antero-lateral FM meningiomas.  This retrospective study included 16 consecutive ...

Predicting Anticoagulation Need for Otogenic Intracranial Sinus Thrombosis: A Machine Learning Approach.

 The role of anticoagulation (AC) in the management of otogenic cerebral venous sinus thrombosis (OCVST) remains controversial. Our study aims to bet...

Acceptance of patients towards task-autonomous robotic cochlear implantation: An exploratory study.

BACKGROUND: Recently, task-autonomous image-guided robotic cochlear implantation has been successfully completed in patients. However, no data exist o...

Investigating Pain-Related Avoidance Behavior using a Robotic Arm-Reaching Paradigm.

Avoidance behavior is a key contributor to the transition from acute pain to chronic pain disability. Yet, there has been a lack of ecologically valid...

Miniaturized Circuitry for Capacitive Self-Sensing and Closed-Loop Control of Soft Electrostatic Transducers.

Soft robotics is a field of robotic system design characterized by materials and structures that exhibit large-scale deformation, high compliance, and...

Experienced bedside-assistants improve operative outcomes for surgeons early in their learning curve for robot assisted laparoscopic radical prostatectomy.

Robot-assisted laparoscopic radical prostatectomy (RALP) relies heavily on the bedside assistant (BA). Currently, the relationship between BA experien...

Deep learning based discrimination of soft tissue profiles requiring orthognathic surgery by facial photographs.

Facial photographs of the subjects are often used in the diagnosis process of orthognathic surgery. The aim of this study was to determine whether con...

Accurate and Efficient Intracranial Hemorrhage Detection and Subtype Classification in 3D CT Scans with Convolutional and Long Short-Term Memory Neural Networks.

In this paper, we present our system for the RSNA Intracranial Hemorrhage Detection challenge, which is based on the RSNA 2019 Brain CT Hemorrhage dat...

Deep-learning-based enhanced optic-disc photography.

Optic-disc photography (ODP) has proven to be very useful for optic nerve evaluation in glaucoma. In real clinical practice, however, limited patient ...

Robust edge-based biomarker discovery improves prediction of breast cancer metastasis.

BACKGROUND: The abundance of molecular profiling of breast cancer tissues entailed active research on molecular marker-based early diagnosis of metast...

A deep learning-based system for identifying differentiation status and delineating the margins of early gastric cancer in magnifying narrow-band imaging endoscopy.

BACKGROUND : Accurate identification of the differentiation status and margins for early gastric cancer (EGC) is critical for determining the surgical...

Comments on: Lower Incidence of Postoperative Pulmonary Complications Following Robot-Assisted Minimally Invasive Esophagectomy for Esophageal Cancer: Propensity Score-Matched Comparison to Conventional Minimally Invasive Esophagectomy.

An entropy-based approach to detect and localize intraoperative bleeding during minimally invasive surgery.

BACKGROUND: During minimally invasive surgery (either robotic or traditional laparoscopic), vascular injuries may occur because of inadvertent surgica...

Machine learning prediction of the adverse outcome for nontraumatic subarachnoid hemorrhage patients.

OBJECTIVE: Subarachnoid hemorrhage (SAH) is often devastating with increased early mortality, particularly in those with presumed delayed cerebral isc...

Public Perceptions of Artificial Intelligence and Robotics in Medicine.

To understand better the public perception and comprehension of medical technology such as artificial intelligence (AI) and robotic surgery. In addit...

Artificial intelligence in cardiothoracic surgery.

The tremendous and rapid technological advances that humans have achieved in the last decade have definitely impacted how surgical tasks are performed...

Predicting complete cytoreduction for advanced ovarian cancer patients using nearest-neighbor models.

BACKGROUND: The foundation of modern ovarian cancer care is cytoreductive surgery to remove all macroscopic disease (R0). Identification of R0 resecti...

Predicting Procedure Step Performance From Operator and Text Features: A Critical First Step Toward Machine Learning-Driven Procedure Design.

OBJECTIVE: The goal of this study is to assess machine learning for predicting procedure performance from operator and procedure characteristics.

3D Deep Neural Network Segmentation of Intracerebral Hemorrhage: Development and Validation for Clinical Trials.

Intracranial hemorrhage (ICH) occurs when a blood vessel ruptures in the brain. This leads to significant morbidity and mortality, the likelihood of w...