Peptic Ulcer Disease

[Robot-assisted laparoscopic total hysterectomy in a patient with giant uterine fibroids and complex pelvic adhesions: a case report].

We report a case of giant hysteromyoma and complex pelvic adhesion treated by robotic assisted laparoscopic total hysterectomy and bilateral salpingectomy. The patient was diagnosed with uterine fibroids after physical examination in 1998 but did not receive any treatment, and regular examinations reported progressive growth of the fibroids. Ultrasound suggested multiple uterine fibroids, and pelv...

Detecting spatially co-expressed gene clusters with functional coherence by graph-regularized convolutional neural network.

MOTIVATION: Clustering spatial-resolved gene expression is an essential analysis to reveal gene activities in the underlying morphological context by their functional roles. However, conventional clustering analysis does not consider gene expression co-localizations in tissue for detecting spatial expression patterns or functional relationships among the genes for biological interpretation in the ...

InDeep: 3D fully convolutional neural networks to assist in silico drug design on protein-protein interactions.

MOTIVATION: Protein-protein interactions (PPIs) are key elements in numerous biological pathways and the subject of a growing number of drug discovery...

Identification of Ulcers and Erosions by the Novel Pillcam™ Crohn's Capsule Using a Convolutional Neural Network: A Multicentre Pilot Study.

BACKGROUND AND AIMS: Capsule endoscopy is a central element in the management of patients with suspected or known Crohn's disease. In 2017, PillCam™ C...

DeepTrio: a ternary prediction system for protein-protein interaction using mask multiple parallel convolutional neural networks.

MOTIVATION: Protein-protein interaction (PPI), as a relative property, is determined by two binding proteins, which brings a great challenge to design...

The Use of Machine Learning in MicroRNA Diagnostics: Current Perspectives.

MicroRNAs constitute small non-coding RNAs that play a pivotal role in regulating the translation and degradation of mRNA and have been associated wit...

Structure-aware protein-protein interaction site prediction using deep graph convolutional network.

MOTIVATION: Protein-protein interactions (PPI) play crucial roles in many biological processes, and identifying PPI sites is an important step for mec...

PhosIDN: an integrated deep neural network for improving protein phosphorylation site prediction by combining sequence and protein-protein interaction information.

MOTIVATION: Phosphorylation is one of the most studied post-translational modifications, which plays a pivotal role in various cellular processes. Rec...

Construction of a 5-feature gene model by support vector machine for classifying osteoporosis samples.

Osteoporosis is a progressive bone disease in the elderly and lacks an effective classification method of patients. This study constructed a gene sign...

[Preliminary application of transoral robotic thyroidectomy: experience from an initial 30 cases].

To examine the surgical outcome of transoral robotic thyroidectomy. Clinic data of total 30 cases of transoral robotic thyroidectomy at the Departme...

Artificial intelligence in musculoskeletal conditions.

Artificial intelligence (AI) is an iterative process by which information is captured, transformed into knowledge and processed to produce adaptive ch...

Identification of viral-mediated pathogenic mechanisms in neurodegenerative diseases using network-based approaches.

During the course of a viral infection, virus-host protein-protein interactions (PPIs) play a critical role in allowing viruses to replicate and survi...

Improved prediction of protein-protein interaction using a hybrid of functional-link Siamese neural network and gradient boosting machines.

In this paper, for accurate prediction of protein-protein interaction (PPI), a novel hybrid classifier is developed by combining the functional-link S...

End-to-End Neural Network for Feature Extraction and Cancer Diagnosis of In Vivo Fluorescence Lifetime Images of Oral Lesions.

In contrast to previous studies that focused on classical machine learning algorithms and hand-crafted features, we present an end-to-end neural netwo...

Predicting the Aortic Aneurysm Postoperative Risks Based on Russian Integrated Data.

This article describes the results of feature extraction from unstructured medical records and prediction of postoperative complications for patients ...

GraphSynergy: a network-inspired deep learning model for anticancer drug combination prediction.

OBJECTIVE: To develop an end-to-end deep learning framework based on a protein-protein interaction (PPI) network to make synergistic anticancer drug c...

Stretchable origami robotic arm with omnidirectional bending and twisting.

Inspired by the embodied intelligence observed in octopus arms, we introduce magnetically controlled origami robotic arms based on Kresling patterns f...

Current status and future perspectives of computational studies on human-virus protein-protein interactions.

The protein-protein interactions (PPIs) between human and viruses mediate viral infection and host immunity processes. Therefore, the study of human-v...

A survey on computational models for predicting protein-protein interactions.

Proteins interact with each other to play critical roles in many biological processes in cells. Although promising, laboratory experiments usually suf...

SMMPPI: a machine learning-based approach for prediction of modulators of protein-protein interactions and its application for identification of novel inhibitors for RBD:hACE2 interactions in SARS-CoV-2.

Small molecule modulators of protein-protein interactions (PPIs) are being pursued as novel anticancer, antiviral and antimicrobial drug candidates. W...