Peptic Ulcer Disease

Identifying the active ingredients of carbonized Typhae Pollen by spectrum-effect relationship combined with MBPLS, PLS, and SVM algorithms.

Typhae Pollen (TP) and its carbonized product (carbonized Typhae Pollen, CTP), as cut-and-dried herbal drugs, have been widely used in the form of slices in clinical settings. However, the two drugs exhibit a great difference in terms of their clinical efficacy, for TP boasts an effect of removing blood stasis and promoting blood circulation, while CTP typically presents a hemostatic function. Sin...

Impact of robotic and open surgery on patient wound complications in gastric cancer surgery: A meta-analysis.

This meta-analysis is intended to evaluate the effect of both robotic and open-cut operations on postoperative complications of stomach carcinoma. From the earliest date until June 2023, a full and systemic search has been carried out on four main databases with keywords extracted from 'Robot', 'Gastr' and 'Opene'. The ROBINS-I instrument has been applied to evaluate the risk of bias in nonrandomi...

Non-endoscopic Applications of Machine Learning in Gastric Cancer: A Systematic Review.

PURPOSE: Gastric cancer is an important health burden characterized by high prevalence and mortality rate. Upper gastrointestinal endoscopy coupled wi...

Effect of amoxicillin and clindamycin on the gene expression of markers involved in osteoblast physiology.

BACKGROUND/PURPOSE: Amoxicillin and clindamycin are the most effective decontaminants for intraoral bone grafts before their application in bone regen...

Artificial intelligence in digestive endoscopy: recent advances.

PURPOSE OF REVIEW: With the incessant advances in information technology and its implications in all domains of our life, artificial intelligence (AI)...

Systematical analysis of underlying markers associated with Marfan syndrome via integrated bioinformatics and machine learning strategies.

Marfan syndrome (MFS) is a hereditary disease with high mortality. This study aimed to explore peripheral blood potential markers and underlying mecha...

Impact of Additional Administration of von Willebrand Factor Concentrates to Thrombocyte Transfusion in Perioperative Bleeding in Cardiac Surgery.

BACKGROUND: Von Willebrand factor (vWF) is an important part of blood coagulation since it binds platelets to each other and to endothelial cells. In ...

Deep learning-based prediction model for diagnosing gastrointestinal diseases using endoscopy images.

BACKGROUND: Gastrointestinal (GI) infections are quite common today around the world. Colonoscopy or wireless capsule endoscopy (WCE) are noninvasive ...

Assisted documentation as a new focus for artificial intelligence in endoscopy: the precedent of reliable withdrawal time and image reporting.

BACKGROUND : Reliable documentation is essential for maintaining quality standards in endoscopy; however, in clinical practice, report quality varies....

Recent Advances in Deep Learning for Protein-Protein Interaction Analysis: A Comprehensive Review.

Deep learning, a potent branch of artificial intelligence, is steadily leaving its transformative imprint across multiple disciplines. Within computat...

Emerging Pharmacotherapeutic Strategies to Overcome Undruggable Proteins in Cancer.

Targeted therapies in cancer treatment can improve efficacy and reduce adverse effects by altering the tissue exposure of specific biomolecules. Howe...

Mastectomy with Reconstruction Including Robotic Endoscopic Surgery (MARRES): a prospective cohort study of the Korea Robot-Endoscopy Minimal Access Breast Surgery Study Group (KoREa-BSG) and Korean Breast Cancer Study Group (KBCSG).

BACKGROUND: Robotic nipple-sparing mastectomy (RNSM) has emerged as a new treatment option for breast cancer and risk-reducing mastectomy (RRM) for wo...

Pangolin-inspired untethered magnetic robot for on-demand biomedical heating applications.

Untethered magnetic miniature soft robots capable of accessing hard-to-reach regions can enable safe, disruptive, and minimally invasive medical proce...

Application of machine learning to predict postoperative gastrointestinal bleed in bariatric surgery.

BACKGROUND: Postoperative gastrointestinal bleeding (GIB) is a rare but serious complication of bariatric surgery. The recent rise in extended venous ...

[Robotics in thoracic surgery].

The increasing diffusion of the robotic-assisted technique in thoracic surgery (RATS) in Germany was initially delayed in comparison with other countr...

Artificial intelligence-aided optical imaging for cancer theranostics.

The use of artificial intelligence (AI) to assist biomedical imaging have demonstrated its high accuracy and high efficiency in medical decision-makin...

Geometric graph neural networks on multi-omics data to predict cancer survival outcomes.

The advance of sequencing technologies has enabled a thorough molecular characterization of the genome in human cancers. To improve patient prognosis ...

Sequence-based machine learning method for predicting the effects of phosphorylation on protein-protein interactions.

Protein phosphorylation, catalyzed by kinases, is an important biochemical process, which plays an essential role in multiple cell signaling pathways....

Protein-Protein Interaction Sites Prediction Using Batch Normalization Based CNNs and Oversampling Method Borderline-SMOTE.

The recognition of protein-protein interaction sites (PPIs) is beneficial for the interpretation of protein functions and the development of new drugs...

Applying deep learning to iterative screening of medium-sized molecules for protein-protein interaction-targeted drug discovery.

We combined a library of medium-sized molecules with iterative screening using multiple machine learning algorithms that were ligand-based, which resu...