AIMC Topic: Humans

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The learning curve of laparoscopic, robot-assisted and transanal total mesorectal excisions: a systematic review.

Surgical endoscopy
BACKGROUND: The standard treatment of rectal carcinoma is surgical resection according to the total mesorectal excision principle, either by open, laparoscopic, robot-assisted or transanal technique. No clear consensus exists regarding the length of ...

Can a flexible surgical robot be used in the pediatric population: A feasibility study.

International journal of pediatric otorhinolaryngology
OBJECTIVES: Transoral robotic surgery in adults confers excellent results and decreased morbidity. Application of these techniques has not yet been rigorously investigated in children. The goal of this study is to evaluate the feasibility of a flexib...

Recent Advances in Touch Sensors for Flexible Wearable Devices.

Sensors (Basel, Switzerland)
Many modern user interfaces are based on touch, and such sensors are widely used in displays, Internet of Things (IoT) projects, and robotics. From lamps to touchscreens of smartphones, these user interfaces can be found in an array of applications. ...

CancerNet: a unified deep learning network for pan-cancer diagnostics.

BMC bioinformatics
BACKGROUND: Despite remarkable advances in cancer research, cancer remains one of the leading causes of death worldwide. Early detection of cancer and localization of the tissue of its origin are key to effective treatment. Here, we leverage technolo...

Deep learning models for forecasting dengue fever based on climate data in Vietnam.

PLoS neglected tropical diseases
BACKGROUND: Dengue fever (DF) represents a significant health burden in Vietnam, which is forecast to worsen under climate change. The development of an early-warning system for DF has been selected as a prioritised health adaptation measure to clima...

Single-Cell Sequencing Analysis and Multiple Machine Learning Methods Identified G0S2 and HPSE as Novel Biomarkers for Abdominal Aortic Aneurysm.

Frontiers in immunology
Identifying biomarkers for abdominal aortic aneurysms (AAA) is key to understanding their pathogenesis, developing novel targeted therapeutics, and possibly improving patients outcomes and risk of rupture. Here, we identified AAA biomarkers from publ...

Deep Learning-Based Magnetic Resonance Imaging in Diagnosis and Treatment of Intracranial Aneurysm.

Computational and mathematical methods in medicine
This study was focused on the positioning of the intracranial aneurysm in the magnetic resonance imaging (MRI) images using the deep learning-based U-Net model, to realize the computer-aided diagnosis of the intracranial aneurysm. First, a network wa...

Value of 4D CT Angiography Combined with Whole Brain CT Perfusion Imaging Feature Analysis under Deep Learning in Imaging Examination of Acute Ischemic Stroke.

Computational intelligence and neuroscience
This study was aimed at investigating the application of deep learning 4D computed tomography angiography (CTA) combined with whole brain CT perfusion (CTP) imaging in acute ischemic stroke (AIS). A total of 46 patients with ischemic stroke were sele...

Artificial Intelligence-Based Semisupervised Self-Training Algorithm in Pathological Tissue Image Segmentation.

Computational intelligence and neuroscience
In the field of medical image processing, due to the differences in tissues, organs, and imaging methods, obtained medical images have significant differences. With the development of intelligence in medicine, an increasing number of computing optimi...