GERD

[Exploring the therapeutic targets and molecular mechanisms of pimecrolimus in the treatment of oral lichen planus based on network pharmacology, machine learning, and molecular docking].

Objective: To systematically investigate the potential targets and therapeutic mechanisms of pimecrolimus in the treatment of oral lichen planus (OLP) using network pharmacology, machine learning, and molecular docking approaches. Methods: Pimecrolimus and OLP-related targets were retrieved from SwissTargetPrediction, Comparative Toxicogenomics Database, and GeneCards database. Intersecting genes ...

A confidence-based, artificial intelligence pathology model for diagnosis of intrahepatic cholangiocarcinoma.

BACKGROUND: Intrahepatic cholangiocarcinoma (ICCA) is a rare but highly lethal adenocarcinoma arising within the hepatic parenchyma. Diagnosis presents a significant clinical challenge as the histological features of ICCA substantially overlap with those of metastatic liver cancers. This diagnostic ambiguity often necessitates extensive and costly exclusionary investigations, such as upper and low...

Identifying Shared Diagnostic Genes and Underlying Mechanisms Between Skin Exposure to Air Pollution and Skin Barrier Damage: A Bioinformatics Approach.

Air pollution poses a significant threat to skin health, contributing to inflammation, aging, and disruption of the epidermal barrier. This study aims...

Integrating Artificial Intelligence into Endoscopy Training.

As artificial intelligence (AI) becomes integrated into gastrointestinal endoscopy, training programs must adapt to prepare learners for AI-assisted p...

An AI-based approach accelerates the discovery of protein-protein interaction modulators targeting NCS-1.

Drug repurposing is an efficient strategy to accelerate the identification of therapeutic compounds by finding new uses for existing drugs. Here, we l...

Development and validation of a multimodal deep learning model for early esophageal squamous neoplasia detection and invasion depth prediction.

Early detection of esophageal squamous cell carcinoma (ESCC) is critical for optimizing patient outcomes. Magnifying endoscopy and endoscopic ultrason...

Solution-Processed Optoelectronic Fusion-Upconversion Devices for Intelligent Perception and Communication.

The rapid growth of the artificial intelligence of things (AIoT) demands multifunctional sensors that deliver intuitive visuals and machine-readable s...

Digital Microscopy in the Endoscopy Suite: A Reference Standard for Colorectal Polyp Size Measurement.

BACKGROUND AND STUDY AIMS: Accurate determination of colorectal polyp size is critical for surveillance recommendations and for generating reliable gr...

Initial Experience With Automated 3D Color Flow Quantification of Mitral Regurgitation.

Accurate quantification of mitral regurgitation (MR) is essential for preprocedural evaluation and intraprocedural decision-making during transcathete...

Interpretable machine learning model for predicting the risk of dysphagia in patients after cardiac surgery.

BACKGROUND: Dysphagia is recognized as one of the most common severe complications following cardiac surgery, with the potential to result in adverse ...

Dysphagia optimized knowledge-based planning for head and neck cancer.

PURPOSE: Swallowing dysfunction after radiotherapy (RT) is often linked to pharyngeal mucosal damage. This study aimed to develop a dysphagia-optimize...

Integrated Single-Cell and Bulk Transcriptome Analysis Reveals the Prognostic Significance and Immune Regulatory Mechanisms of Sialylation in Hepatocellular Carcinoma.

Liver Hepatocellular Carcinoma (LIHC) is a high-mortality primary liver cancer. Its treatment and prognosis are highly dependent on disease stage and ...

Evaluating the cost-effectiveness of artificial intelligence in Barrett's surveillance.

Artificial intelligence (AI) has emerged as a promising tool to detect early dysplasia in Barrett's esophagus (BE). However, the cost-effectiveness of...

Machine learning-based identification of potential diagnostic signatures in spinal cord injury.

STUDY DESIGN: Bioinformatics analysis. OBJECTIVES: To explore the diagnostic signatures for patients with spinal cord injury (SCI). SETTING: Shenyang,...

Identification of extracellular matrix stiffness-related genes in human scleral fibroblasts through bioinformatics analysis and machine learning.

BACKGROUND: Scleral extracellular matrix (ECM) remodeling plays a key role in myopia development. This study aims to identify ECM stiffness-related ge...

CystoDS: a multiclass endoscopy image dataset for artificial intelligence-assisted bladder cancer detection.

Cystoscopy is a common endoscopic procedure used for the visual inspection of the lower urinary tract, particularly for the detection and surveillance...

Ensemble model assisted classification of gastrointestinal bleeding using wireless capsule endoscopy.

Wireless Capsule Endoscopy (WCE) is a useful method for imaging the intestines painlessly and looking into gastrointestinal tract diseases. The invest...

Generative AI Uncovers Novel Chrebp/Txnip Axis Inhibitors with Potential Anti-inflammatory Activity.

Type 2 diabetes is driven in part by metabolic inflammation, where activation of the Chrebp/Txnip axis promotes NLRP3 inflammasome assembly, leading t...

Diagnosis of Gastric Intestinal Metaplasia: Histology, Endoscopy, and Artificial Intelligence.

Background Gastric intestinal metaplasia (GIM) is a well-established precancerous lesion and key biomarker for assessing the risk of gastric cancer. H...

Endoscopic Ultrasound for the Management of Pancreatic Neuroendocrine Tumors: Diagnosis, Treatment, and Future Perspectives.

Pancreatic neuroendocrine tumors (PanNETs) are increasingly diagnosed, reflecting greater clinical awareness, improved imaging, and revised classifica...