AIMC Topic: Humans

Clear Filters Showing 50451 to 50460 of 95995 articles

A robot goes to rehab: a novel gamified system for long-term stroke rehabilitation using a socially assistive robot-methodology and usability testing.

Journal of neuroengineering and rehabilitation
BACKGROUND: Socially assistive robots (SARs) have been proposed as a tool to help individuals who have had a stroke to perform their exercise during their rehabilitation process. Yet, to date, there are no data on the motivating benefit of SARs in a ...

Heart rate estimation from ballistocardiographic signals using deep learning.

Physiological measurement
Ballistocardiography (BCG) is an unobtrusive approach for cost-effective and patient-friendly health monitoring. In this work, deep learning methods are used for heart rate estimation from BCG signals and are compared against five digital signal proc...

Data-driven identification of complex disease phenotypes.

Journal of the Royal Society, Interface
Disease interaction in multimorbid patients is relevant to treatment and prognosis, yet poorly understood. In the present work, we combine approaches from network science, machine learning and computational phenotyping to assess interactions between ...

The Effect of Applying Robot-Assisted Task-Oriented Training Using Human-Robot Collaborative Interaction Force Control Technology on Upper Limb Function in Stroke Patients: Preliminary Findings.

BioMed research international
Stroke is one of the leading causes of death and the primary cause of acquired disability worldwide. Many stroke survivors have difficulty using their upper limbs, which have important functional roles in the performance of daily life activities. Con...

Deep Learning-Based CT Image Characteristics and Postoperative Anal Function Restoration for Patients with Complex Anal Fistula.

Journal of healthcare engineering
OBJECTIVE: This study aimed to optimize the CT images of anal fistula patients using a convolutional neural network (CNN) algorithm to investigate the anal function recovery.

Machine learning predicts treatment sensitivity in multiple myeloma based on molecular and clinical information coupled with drug response.

PloS one
Providing treatment sensitivity stratification at the time of cancer diagnosis allows better allocation of patients to alternative treatment options. Despite many clinical and biological risk markers having been associated with variable survival in c...

Test clamp procedure in robot-assisted partial nephrectomy: is it a safe procedure?

Journal of robotic surgery
We performed test clamp procedure in robot-assisted partial nephrectomy (RAPN) to prevent massive bleeding during tumor resection and to omit dissection of non-feeding arteries around the tumor. We subsequently analyzed the safety and usefulness of t...

Automatic Detection of Covid-19 with Bidirectional LSTM Network Using Deep Features Extracted from Chest X-ray Images.

Interdisciplinary sciences, computational life sciences
Coronavirus disease, which comes up in China at the end of 2019 and showed different symptoms in people infected, affected millions of people. Computer-aided expert systems are needed due to the inadequacy of the reverse transcription-polymerase chai...

The use of deep learning towards dose optimization in low-dose computed tomography: A scoping review.

Radiography (London, England : 1995)
INTRODUCTION: Low-dose computed tomography tends to produce lower image quality than normal dose computed tomography (CT) although it can help to reduce radiation hazards of CT scanning. Research has shown that Artificial Intelligence (AI) technologi...

Robot-assisted Exploration of Somatic Nerves in the Pelvis and Transection of the Sacrospinous Ligament for Alcock Canal Syndrome.

Journal of minimally invasive gynecology
STUDY OBJECTIVE: Some articles have reported the surgical management of Alcock canal syndrome (ACS) using the transperineal [1], transgluteal [2], or conventional laparoscopic approach [3,4]. In 2015, Rey and Oderda [5] reported the first robotic neu...