Latest AI and machine learning research in surgery for healthcare professionals.
OBJECTIVE: Focal cortical dysplasia (FCD) is a major pathology in patients undergoing surgical resection to treat pharmacoresistant epilepsy. Magnetic resonance imaging (MRI) postprocessing methods may provide essential help for detection of FCD. In this study, we utilized surface-based MRI morphometry and machine learning for automated lesion detection in a mixed cohort of patients with FCD type ...
INTRODUCTION: Mortality and morbidity following surgery are pressing public health concerns in the USA. Traditional prediction models for postoperative adverse outcomes demonstrate good discrimination at the population level, but the ability to forecast an individual patient's trajectory in real time remains poor. We propose to apply machine learning techniques to perioperative time-series data to...
Accurate planning transfer is a prerequisite for successful operative care. For different applications, diverse computer-assisted systems have been de...
Identifying trauma patients at risk of imminent hemorrhagic shock is a challenging task in intraoperative and battlefield settings given the variabili...
Collective cell migration, in which cells migrate as a group, is fundamental in many biological and pathological processes. There is increasing intere...
This paper presents the development of a biomimetic robotic fish that uses an integrated oscillation and jet propulsive mechanism to enable good swimm...
OBJECTIVE: To compare the effect of simulator functional fidelity (manikin vs a Dynamic Haptic Robotic Trainer [DHRT]) and personalized feedback on su...
PURPOSE: Surgical performance is critical for clinical outcomes. We present a novel machine learning (ML) method of processing automated performance m...
Flexible robotic catheters are an emerging technology which provide an elegant solution to the challenges of conventional endovascular intervention. O...
A large amount of hemiplegic survivors are suffering from motor impairment. Ankle rehabilitation exercises act an important role in recovering patient...
The measurement of wrist passive ranges of motion (ROMs) can provide insight into improvements and allow for effective monitoring during a rehabilitat...
BACKGROUND: Surgical robot systems have been used in laparoendoscopic single-site surgery (LESS) to improve patient outcomes. A magnetic anchoring sur...
The objective of this study was to introduce a new machine learning guided by outcome of resective epilepsy surgery defined as the presence/absence of...
Colorectal cancer (CRC) is one of the most daunting diseases due to its increasing worldwide prevalence, which requires imperative development of mini...
In order to properly control rehabilitation robotic devices, the measurement of interaction force and motion between patient and robot is an essential...
With the development of deep neural networks, many object detection frameworks have shown great success in the fields of smart surveillance, self-driv...
This study investigated whether parameters derived from hand motions of expert and novice surgeons accurately and objectively reflect laparoscopic sur...
Segmentation of axon and myelin from microscopy images of the nervous system provides useful quantitative information about the tissue microstructure,...
Possible world has shown to be effective for handling various types of data uncertainty in uncertain data management. However, few uncertain data clus...