Peptic Ulcer Disease

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 mechanisms in MFS via a series bioinformatics and machine learning analysis. First, we downloaded two MFS datasets from the GEO database. A total of 215 differentially expressed genes (DEGs) and 78 differentially expressed miRNAs (DEMs) were identified vi...

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 traumatic and surgical haemorrhage, both blood cells and plasmatic factors are consumed, leading to consumption coagulopathy and fluid resuscitation. This often results in large amounts of crystalloids and blood products being infused. Additional adm...

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...

Artificial intelligence in intestinal polyp and colorectal cancer prediction.

Artificial intelligence (AI) algorithms and their application to disease detection and decision support for healthcare professions have greatly evolve...

Using a stacked ensemble learning framework to predict modulators of protein-protein interactions.

Identifying small molecule protein-protein interaction modulators (PPIMs) is a highly promising and meaningful research direction for drug discovery, ...

Robotic instruments outside the surgical field can cause problems: A case of critical bleeding during robotic distal pancreatectomy.

Robotic surgery has technical advantages including high optical magnification and articulation of forceps. However, the surgical field tends to be nar...

CG02N Analyzer Accurately Measures Fibrinogen Level in Whole Blood in the Presence of Low- or High-Dose Heparin.

Rapid fibrinogen (Fbg) evaluation is important in patients with massive bleeding during severe trauma and those undergoing major surgery. However, the...

Targeting Protein-Protein Interfaces with Peptides: The Contribution of Chemical Combinatorial Peptide Library Approaches.

Protein-protein interfaces play fundamental roles in the molecular mechanisms underlying pathophysiological pathways and are important targets for the...