Latest AI and machine learning research in surgery for healthcare professionals.
The adoption of brain-computer interfaces (BCIs) has significantly increased in various application domains, particularly in the field of controlling robotic systems through motor imagery. The article contributes in two primary ways: 1) validating the effectiveness of using a minimally invasive electroencephalography (EEG) device combined with machine learning techniques to control fundamental mov...
Increasing interest surrounds the use of robotic and computer technologies for precise endovascular interventions. However, a limitation in current robotic procedures is the reliance on 2D fluoroscopy for surgical navigation and lack of haptic guidance. In addressing this, we present an improved guidance framework for CathBot, our MR-compatible endovascular robot. This includes visual guidance thr...
Swallowing is a pivotal physiological function for human sustenance and hydration. Dysfunctions, termed dysphagia, necessitate prompt and precise diag...
This paper proposes a deep-learning computer vision algorithm to estimate hand roll angles for metric-based assessment of surgical suturing skills. Th...
As the worldwide incidence of stroke increases, supernumerary robotic limbs (SRLs), more specifically supernumerary robotic fingers (SRFs), present a ...
This paper reports an innovative and instant method for tumor detection. We delineate the tactile signal matrixes of tumor tissue with varying stiffne...
Invasive brain-machine interfaces can help restore function through the control of external devices while the addition of intracortical microstimulati...
Shoulder dislocations are the most common dislocations and there is a demand for a novel traction device for reducing anterior shoulder dislocations, ...
Partial nephrectomy, the gold standard treatment for renal tumors, is performed with clamping of the renal arteries, in order to interrupt the blood f...
Meningiomas are the most prevalent benign intracranial tumors, and surgical intervention is the primary treatment. The physical characteristics of men...
Artificial intelligence & Computer vision have the potential to improve surgical training, especially for minimally invasive surgery by analyzing intr...
The goal of the present pilot investigation is to examine the effects of 8 weeks of supervised, over-ground gait training using a robotic exoskeleton ...
A calibration method for gelatin-graphite-based soft sensors is proposed. This approach uses convolutional deep learning approaches that account for a...
450,000 children with epilepsy in the United States suffer lifelong disability and are at risk of sudden death. Surgical treatment of epilepsy is limi...
Surgical resection is now the only curative approach for early stage lung cancer patients. However, postoperative complications pose a significant thr...
In minimally invasive surgery, poor needle visualization under ultrasound has been one of the challenges of the surgery. To improve the resulting punc...
The Parallel Continuum Robot (PCR) is an emerging class of soft robotics distinguished by features such as flexibility, safety, compactness, and dexte...
Postoperative complications in surgery are particularly prevalent in laparoscopic procedures, which are difficult for physicians to perform. One compl...
Studying the soft robot-tissue mechanical interaction in muscle stimulation devices poses a significant challenge due to the complex behavior of the m...
Humans are capable of performing intricate and complex tasks, enabling seamless interaction with their surroundings. Therefore, capturing the human de...