GERD

[Enhanced imaging in urological endoscopy].

White light cystoscopy and the concise documentation of pathological findings are standard diagnostic procedures in urology. Additional imaging modalities and technical innovations may support clinicians in the detection of bladder tumors. Modern endoscopy systems provide ultra-high-resolution imaging and the option of digital contrast enhancement. Photodynamic diagnostics and narrow band imaging ...

Immune profile of the tumor microenvironment and the identification of a four-gene signature for lung adenocarcinoma.

The composition and relative abundances of immune cells in the tumor microenvironment are key factors affecting the progression of lung adenocarcinomas (LUADs) and the efficacy of immunotherapy. Using the cancer gene expression dataset from The Cancer Genome Atlas (TCGA) program, we scored stromal and immune cells for tumor purity prediction by CIBERSORT and ESTMATE. Differential expression analys...

Selecting Children with Vesicoureteral Reflux Who are Most Likely to Benefit from Antibiotic Prophylaxis: Application of Machine Learning to RIVUR.

PURPOSE: Continuous antibiotic prophylaxis reduces the risk of recurrent urinary tract infection by 50% in children with vesicoureteral reflux. Howeve...

Artificial intelligence: Thinking outside the box.

Artificial intelligence (AI) for luminal gastrointestinal endoscopy is rapidly evolving. To date, most applications have focused on colon polyp detect...

Pitfalls in training and validation of deep learning systems.

The number of publications in endoscopic journals that present deep learning applications has risen tremendously over the past years. Deep learning ha...

Zoom in Lesions for Better Diagnosis: Attention Guided Deformation Network for WCE Image Classification.

Wireless capsule endoscopy (WCE) is a novel imaging tool that allows noninvasive visualization of the entire gastrointestinal (GI) tract without causi...

Predicting spatial esophageal changes in a multimodal longitudinal imaging study via a convolutional recurrent neural network.

Acute esophagitis (AE) occurs among a significant number of patients with locally advanced lung cancer treated with radiotherapy. Early prediction of ...

Identifying early gastric cancer under magnifying narrow-band images with deep learning: a multicenter study.

BACKGROUND AND AIMS: Narrow-band imaging with magnifying endoscopy (ME-NBI) has shown advantages in the diagnosis of early gastric cancer (EGC). Howev...

Detection of multiple lesions of gastrointestinal tract for endoscopy using artificial intelligence model: a pilot study.

BACKGROUND: This study was aimed to develop a computer-aided diagnosis (CAD) system with deep-learning technique and to validate its efficiency on det...

A deep learning framework for quality assessment and restoration in video endoscopy.

Endoscopy is a routine imaging technique used for both diagnosis and minimally invasive surgical treatment. Artifacts such as motion blur, bubbles, sp...

A real-time system using deep learning to detect and track ureteral orifices during urinary endoscopy.

BACKGROUND AND OBJECTIVE: To automatically identify and locate various types and states of the ureteral orifice (UO) in real endoscopy scenarios, we d...

Early gastric cancer and Artificial Intelligence: Is it time for population screening?

Gastric cancer is a common cause of death worldwide and its early detection is crucial to improve its prognosis. Its incidence varies throughout count...

Triage of documents containing protein interactions affected by mutations using an NLP based machine learning approach.

BACKGROUND: Information on protein-protein interactions affected by mutations is very useful for understanding the biological effect of mutations and ...

Artificial intelligence automates and augments baseline impedance measurements from pH-impedance studies in gastroesophageal reflux disease.

BACKGROUND: Artificial intelligence (AI) has potential to streamline interpretation of pH-impedance studies. In this exploratory observational cohort ...

A Multi-View Deep Neural Network Model for Chemical-Disease Relation Extraction From Imbalanced Datasets.

Understanding the chemical-disease relations (CDR) is a crucial task in various biomedical domains. Manual mining of these information from biomedical...

Artificial intelligence in endoscopy: Present and future perspectives.

Artificial intelligence (AI) has been attracting considerable attention as an important scientific topic in the field of medicine. Deep-leaning (DL) t...

Pediatric Adenoidectomy: A Comparative Study Between Cold Curettage and Coblation Technique.

The objective of the study was to assess endoscopic coblation adenoidectomy and conventional cold curettage adenoidectomy in terms of safety and effic...

Artificial intelligence that determines the clinical significance of capsule endoscopy images can increase the efficiency of reading.

Artificial intelligence (AI), which has demonstrated outstanding achievements in image recognition, can be useful for the tedious capsule endoscopy (C...

A Gratifying Step forward for the Application of Artificial Intelligence in the Field of Endoscopy: A Narrative Review.

BACKGROUND: Endoscopy is the optimal choice of diagnosis of gastrointestinal (GI) diseases. Following the advancements made in medical technology, dif...

Realizing 5G- and AI-based doctor-to-doctor remote diagnosis: opportunities, challenges, and prospects.

Fifth Generation (5G) mobile communications technology became available in Japan as of the end of March 2020. The Ministry of Internal Affairs and Com...