Inflammatory Bowel Disease

Machine Learning Algorithms to Accelerate Etiological Diagnosis of Congenital Disorders of Adrenal Steroidogenesis.

BACKGROUND: Early and accurate etiological diagnosis of congenital disorders of adrenal steroidogenesis (CDAS) is critical as timely targeted management can prevent life-threatening complications and improve long-term outcomes. OBJECTIVE: To develop and validate a machine learning-assisted decision tree model for classifying CDAS using plasma steroid hormone profiles quantified by liquid chromatog...

Repurposing Non-oncologic Drugs via Targeted Nanocarriers for Cancer Therapy: Mechanisms, Synergistic Combinations, and Clinical Translation.

The urgent need for innovative cancer therapies has driven increasing interest in repurposing drugs originally developed for non-oncological diseases. Several FDA-approved and clinically investigated agents, including mesalamine, celecoxib, gliclazide, metformin, itraconazole, and doxycycline, have shown anticancer potential through diverse mechanisms. However, despite their therapeutic potential,...

Corneal nerve regeneration: treatments and monitoring approaches.

BACKGROUND: Diagnostics and therapeutics for corneal nerve pathologies are rapidly evolving, with continual advancements in imaging, laser, machine le...

Implementation of a prospective video databank for artificial intelligence model development, validation and clinical outcomes research in gastrointestinal endoscopy.

BACKGROUND AND AIMS: High-quality, annotated datasets are fundamental to clinical research and artificial intelligence (AI) model development. Existin...

Structure-based virtual screening identifies potential endogenous ligands of the human bitter taste receptor TAS2R46.

The sensing of bitter taste mediated by TAS2Rs serves as a defense mechanism against potentially harmful substances. The expression of TAS2Rs in extra...

Development of a LASSO-based machine learning model for relapse prediction in lupus nephritis.

OBJECTIVE: To identify the predictors of renal relapse in patients with lupus nephritis (LN) and develop a predictive model. METHODS: The patients wit...

Effects of biologic and targeted synthetic disease modifying antirheumatic drugs (b/tsDMARDs) on patient-reported outcome domains in rheumatoid arthritis: a systematic review and network meta-analyses.

INTRODUCTION: Evidence from head-to-head comparisons of biologic/targeted synthetic disease-modifying antirheumatic drugs (b/tsDMARDs) on patient-repo...

Identification of small-molecule TNF-α inhibitor candidates using machine learning-guided screening and multiscale molecular modelling.

Lumbar disc herniation (LDH) is a major cause of chronic low back pain, in which tumor necrosis factor-alpha (TNF-α) plays a central role in inflammat...

Predicting High-Risk Colorectal Polyps in African Americans Using Pre-colonoscopy Clinical Features: Machine Learning Model Development and Temporal Validation.

PURPOSE: Risk stratification for advanced colorectal polyps typically relies on colonoscopy and/or pathology findings. However, there is growing inter...

Gastrointestinal endoscopic image classification using a hybrid modified inception network and a customized vision transformer with tree growth feature selection.

The Gastrointestinal (GI) tract plays a vital role in digestion by breaking down food into essential nutrients. Disorders such as bleeding lesions, ul...

Artificial intelligence in pediatric endoscopy for hereditary polyposis syndromes: promises and challenges.

PURPOSE OF REVIEW: Children with hereditary polyposis syndromes require long-term endoscopic surveillance to reduce risks of gastrointestinal complica...

Integrating neurobiological markers to prospectively predict adolescent non-suicidal self-injury and suicide attempts: a machine learning approach.

BACKGROUND: Suicide attempts (SA) and non-suicidal self-injury (NSSI) are closely related phenomena, both common in adolescent clinical samples. This ...

Optimising biologic therapy in psoriasis: dose adjustment, treatment duration, and tapering-an expert perspective.

INTRODUCTION: Biologic therapies have transformed the management of moderate-to-severe psoriasis; however, long-term treatment requires optimization s...

Development and validation of the SYSU-score for MRI-based transmural healing assessment in Crohn's disease: a dual-center study.

OBJECTIVES: Standardizing magnetic resonance enterography (MRE)-defined transmural healing (TH) remains challenging in Crohn's disease (CD) despite it...

IBS-CNN: a novel computer vision-based kinship classification model for high-density SNP microarray.

This study addresses multiple challenges in applying forensic genealogy to Chinese populations by exploring novel kinship classification strategies ba...

FD-MSP: feature decoupling network with multi-scale prototypes for domain-adaptive polyp segmentation.

Polyp segmentation in colonoscopy images plays a critical role in the early detection and treatment of colorectal cancer. Although deep learning-based...

Automated extraction of colonoscopy quality indicators from free-text reports using a prompt-based large language model pipeline.

BACKGROUND AND AIMS: Artificial intelligence has increasingly enabled large-scale analysis of clinical documentation, offering new opportunities to im...

Single-cell transcriptomic analysis reveals the T lymphocyte microenvironment and identifies HOPX as a hub gene in membranous nephropathy.

BACKGROUND: Membranous nephropathy (MN) is an autoimmune disease characterized by immune complex deposition and progressive renal function impairment....

Radiomics-based unsupervised clustering and deep learning nomogram for response prediction after neoadjuvant chemotherapy in locally advanced laryngeal cancer.

OBJECTIVES: To develop a nomogram model for individualized prediction of neoadjuvant chemotherapy (NAC) response in locally advanced laryngeal cancer ...

[Construction and validation of a prognostic prediction model for children-onset initial steroid-resistant nephrotic syndrome].

Objective: To analyze the risk factors for poor prognosis in children with steroid-resistant nephrotic syndrome (SRNS) and to construct and validate a...