Inflammatory Bowel Disease

Machine learning prediction of increased healthcare utilization in colectomy for inflammatory bowel disease.

PURPOSE: Healthcare spending for patients with inflammatory bowel disease (IBD) has steadily increased over the past few decades. While some of the increase is due to the rise in the use of biologics, surgery and postoperative care contribute significantly to healthcare spending. We aimed to analyze the preoperative factors associated with increased healthcare resource utilization (HRU) by develop...

Development of a predictive model for postoperative body mass index and diabetes outcomes after metabolic bariatric surgery: retrospective cohort study.

BACKGROUND: Predicting postoperative body mass index (BMI) trajectories and long-term type 2 diabetes (T2D) remission after bariatric surgery remains challenging. Existing models often rely on baseline variables only and fail to incorporate dynamic postoperative changes. This study aimed to develop and validate a multicentre machine-learning framework that predicts individualized BMI trajectories ...

Technical and clinical feasibility of single-use gastroscopy with real-time AI-based quality monitoring and single-use colonoscopy: a prospective two-center study.

BACKGROUND: Single-use gastrointestinal endoscopes eliminate the need for post-procedure reprocessing and have become an area of interest in endoscopi...

Early prediction of joint space narrowing in rheumatoid arthritis using AI-quantified bilateral joint space asymmetry on hand radiography.

PURPOSE: Joint space narrowing (JSN) in rheumatoid arthritis (RA) can progress even during clinical remission. Conventional imaging lacks sensitivity ...

AI-assisted Radiomic Model for Cervical Cancer Recurrence Prediction: A Multicenter Retrospective Study with Experimental Validation.

Purpose To evaluate the value of a nomogram model incorporating clinical parameters, hematologic inflammatory biomarkers, and MRI radiomic features in...

Integrative Genomic and Clinical Profiling of Colorectal Cancer Liver Metastases to Guide Personalized Surgery and Liver Transplantation.

BACKGROUND/AIM: Colorectal cancer liver metastases (CRLM) remain a leading cause of cancer-related mortality. Although hepatic resection is the only e...

Effectiveness of CADe in Colonoscopy for Improved Adenoma and Polyp Detection Under Diverse Clinical Conditions.

BACKGROUND/AIM: Colonoscopy is the gold standard for colorectal cancer prevention, but its effectiveness is limited by missed lesions and operator-dep...

In vitro development of the Autonomous Colonoscope Robot System (ACRS) for fully automated colonoscope insertion.

BACKGROUND: In the field of colonoscopy, robotic systems have been developed to support or replace human operators due to a shortage of trained endosc...

Artificial intelligence (AI)-assisted diagnosis of skin diseases: From image classification to dermatology-specific multimodal clinical reasoning.

Artificial intelligence (AI) in dermatology has moved beyond the early paradigm of single-image classification. Dermatological diagnosis is achieved b...

Identification of distinct subgroups in Chinese patients with Behçet's syndrome via cluster analysis of immune cells and clinical features.

OBJECTIVES: This study aimed to use machine learning to explore Behçet's syndrome (BS) heterogeneity by integrating immunocyte subpopulations and clin...

Identifying coagulation-related biomarkers in steroid-induced osteonecrosis of the femoral head: implications for early diagnosis and treatment.

Steroid-induced osteonecrosis of the femoral head (SONFH) is closely associated with coagulation dysfunction, but its molecular mechanisms remain inco...

Unsupervised Machine Learning of Inflammatory Bowel Disease Case Reports Reveals Decades of Evolving Research Themes.

BACKGROUND AND AIMS: Inflammatory bowel disease (IBD) case reports provide rich longitudinal insights but have rarely been analyzed using quantitative...

The functional relevance of human leukocyte antigens in the development of cord blood derived advanced cellular therapies: A new direction of public cord blood banks.

CBUs have been applied as alternative source of HSCs transplantation. The increasing preference for haploidentical HSC transplantation has resulted in...

The Addition of Computer-Aided Detection (CADe) to Texture and Color Enhancement Imaging (TXI) Does Not Improve Adenoma Detection Rate During Colonoscopy: A Prospective Study.

OBJECTIVES: Early detection and resection of colorectal polyps prevent their progression toward advanced adenocarcinomas. The use of Texture and Color...

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 manageme...

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....

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...