Peptic Ulcer Disease

[A deep learning segmentation model for detecting caries in molar teeth].

This study aimed to build a home use deep learning segmentation model to identify the scope of caries lesions. A total of 494 caries photographs of molars and premolars collected via endoscopy were selected. Subsequently, these photographs were labeled by physicians and underwent segmentation training by using DeepLabv3+, and then verification and evaluation were performed. The mean accuracy was 0...

[Application and progress of artificial intelligence technology in gastric cancer diagnosis and treatment].

Artificial intelligence (AI) is one of the most rapidly evolving fields in biomedicine during the past decade. Represented by radiomics, machine learning and deep neural network, AI has been increasingly favored by researchers due to its ability to obtain feature information and discover the potential relationship between data and medical outcomes from high-throughput medical data. The incidence a...

Edge detection in single multimode fiber imaging based on deep learning.

We propose a new edge detection scheme based on deep learning in single multimode fiber imaging. In this scheme, we creatively design a novel neural n...

Mitigating cold-start problems in drug-target affinity prediction with interaction knowledge transferring.

Predicting the drug-target interaction is crucial for drug discovery as well as drug repurposing. Machine learning is commonly used in drug-target aff...

De novo molecular design with deep molecular generative models for PPI inhibitors.

We construct a protein-protein interaction (PPI) targeted drug-likeness dataset and propose a deep molecular generative framework to generate novel dr...

The Future of Minimally Invasive Spinal Surgery.

Strong forces are pushing minimally invasive spinal surgery (MISS) to the forefront of spine care. Less-invasive surgical techniques have been enabled...

[Our Experience and Technical Improvement in Robot-assisted Cardiac Surgery].

Since 2014, we have used the da Vinci surgical system to perform internal thoracic artery harvest in minimally invasive direct coronary artery bypass ...

[Feasibility and Clinical Benefit of Robot-assisted Minimally Invasive Direct Coronary Artery Bypass Surgery].

In minimally invasive direct coronary artery bypass surgery (MIDCAB), internal mammary artery harvesting is not so easy because of small exposure and ...

Supervised and semi-supervised training of deep convolutional neural networks for gastric landmark detection.

This work focuses on detection of upper gas-trointestinal (GI) landmarks, which are important anatomical areas of the upper GI tract digestive system ...

Analysis of classification tradeoff in deep learning for gastric cancer detection.

This study aimed to build convolutional neural network (CNN) models capable of classifying upper endoscopy images, to determine the stage of infection...

Development of Needle Guide Unit Considering Buckling Bone-Perforation Control Strategy Based on Computed Tomography-Guided Needle Insertion Robot.

A computed tomography (CT)-guided robotic assistance system is useful for needle insertion into metastatic carcinoma of vertebrae, which has limited p...

Utility of a deep learning model and a clinical model for predicting bleeding after endoscopic submucosal dissection in patients with early gastric cancer.

BACKGROUND: Bleeding is one of the major complications after endoscopic submucosal dissection (ESD) in early gastric cancer (EGC) patients. There are ...

[Transoral robotic surgery for treatment of lingual thyroglossal duct cyst].

To investigate the feasibility, safety and efficacy of transoral robotic surgery (TORS) in the treatment of lingual thyroglossal duct cyst (LTGDC). ...

Influence of Robot-Assisted Partial Nephrectomy on Long-Term Renal Function as Assessed Using 99m-Tc DTPA Renal Scintigraphy.

The long-term split renal function after robot-assisted partial nephrectomy (RAPN) is yet to be elucidated. This study aimed to assess long-term rena...

[Development and thoughts of digestive endoscopy in children].

After nearly 40 years of development, digestive endoscopy in children has been widely applied, and it has helped to expand the spectrum of pediatric d...

Learning spatial structures of proteins improves protein-protein interaction prediction.

Spatial structures of proteins are closely related to protein functions. Integrating protein structures improves the performance of protein-protein in...

PRODeepSyn: predicting anticancer synergistic drug combinations by embedding cell lines with protein-protein interaction network.

Although drug combinations in cancer treatment appear to be a promising therapeutic strategy with respect to monotherapy, it is arduous to discover ne...

EGRET: edge aggregated graph attention networks and transfer learning improve protein-protein interaction site prediction.

MOTIVATION: Protein-protein interactions (PPIs) are central to most biological processes. However, reliable identification of PPI sites using conventi...

Persistent spectral based ensemble learning (PerSpect-EL) for protein-protein binding affinity prediction.

Protein-protein interactions (PPIs) play a significant role in nearly all cellular and biological activities. Data-driven machine learning models have...

A systemic review and meta-analysis of the effects of perioperative anticoagulant and antiplatelet therapy on bleeding complications in robot-assisted prostatectomy.

OBJECTIVE: Robot-assisted prostatectomy is commonly performed for the management of prostate cancer. The literature has noted that prostate cancer pat...