Inflammatory Bowel Disease

Selective Glucocorticoid Receptor Modulators of Immune Checkpoint Function

Glucocorticoids (GCs) coordinate immunity, inflammation and metabolism through allosteric regulation of the glucocorticoid receptor (GR) transcription factor. GCs are indispensable anti-inflammatory drugs yet linking specific ligand and receptor structural states to specific biological outcomes has remained a major barrier to designing safer, more selective therapies. Using structure based design,...

Enabling Real-Time Colonoscopic Polyp Segmentation on Commodity CPUs via Ultra-Lightweight Architecture

Early detection of colorectal cancer hinges on real-time, accurate polyp identification and resection. Yet current high-precision segmentation models rely on GPUs, making them impractical to deploy in primary hospitals, mobile endoscopy units, or capsule robots. To bridge this gap, we present the UltraSeg family, operating in an extreme-compression regime (<0.3 M parameters). UltraSeg-108K (0.108 ...

XtraLight-MedMamba for Classification of Neoplastic Tubular Adenomas

Accurate risk stratification of precancerous polyps during routine colonoscopy screenings is essential for lowering the risk of developing colorectal ...

AI quantification of inflammatory and architectural features in ulcerative colitis distinguishes active disease from remission

Background and Aims: Artificial intelligence (AI) is increasingly applied to histological assessment in inflammatory bowel disease (IBD), but most app...

Breast cancer radiogenomics analysis via computational perturbation on AI-driven multi-omics guided image synthesis

Radiogenomics offers a promising non-invasive approach for characterizing breast cancer (BC), yet its progress is often limited by the scarcity of coh...

Learning with Geometric Priors in U-Net Variants for Polyp Segmentation

Accurate and robust polyp segmentation is essential for early colorectal cancer detection and for computer-aided diagnosis. While convolutional neural...

Phi-SegNet: Phase-Integrated Supervision for Medical Image Segmentation

Deep learning has substantially advanced medical image segmentation, yet achieving robust generalization across diverse imaging modalities and anatomi...

Peripheral blood profiles reflecting progenitor lineage balance predict treatment response in chronic myeloid leukemia

Early achievement of deep remission improves patients' outcome in chronic myeloid leukemia (CML) treatment, highlighting the need for predictive indic...

Deep learning-based detection of bacterial swarm motion using a single image.

Motility is a fundamental characteristic of bacteria. Distinguishing between swarming and swimming, the two principal forms of bacterial movement, hol...

Explainable artificial intelligence for prediction of refractory ulcerative colitis: analysis of a Japanese Nationwide Registry.

OBJECTIVE: Ulcerative colitis (UC) is a chronic inflammatory bowel disease for which remission is dependent on corticosteroid (CS) treatment. The dive...

Prediction of remission of pharmacologically treated psychotic depression: A machine learning approach.

BACKGROUND: The combination of antidepressant and antipsychotic medication is an effective treatment for major depressive disorder with psychotic feat...

Effect of Static vs. Conversational AI-Generated Messages on Colorectal Cancer Screening Intent: a Randomized Controlled Trial

Large language model (LLM) chatbots show increasing promise in persuasive communication. Yet their real-world utility remains uncertain, particularl...

CL-Polyp: A Contrastive Learning-Enhanced Network for Accurate Polyp Segmentation

Accurate segmentation of polyps from colonoscopy images is crucial for the early diagnosis and treatment of colorectal cancer. Most existing deep le...

Protocol for a multicenter randomized controlled trial to assess the usefulness of computer-aided detection systems for colonoscopy in colorectal cancer screening in the Asia-Pacific region (project CAD/NCCH2217).

Ensuring the high quality of colonoscopies in colorectal cancer (CRC) screening is essential to reducing CRC. Recently, computer-aided detection syste...

Temporally-Aware Supervised Contrastive Learning for Polyp Counting in Colonoscopy

Automated polyp counting in colonoscopy is a crucial step toward automated procedure reporting and quality control, aiming to enhance the cost-effec...

Mamba Guided Boundary Prior Matters: A New Perspective for Generalized Polyp Segmentation

Polyp segmentation in colonoscopy images is crucial for early detection and diagnosis of colorectal cancer. However, this task remains a significant...

Vedolizumab in inflammatory bowel disease: Real-world outcomes and their prediction with machine learning-the IG-IBD LIVE study.

BACKGROUND AND AIMS: Real-world studies on vedolizumab in inflammatory bowel disease (IBD) are often limited by small sample size and short follow-up....

Clinical Utility Findings of a Transcriptomic Psoriasis Biologic Test Demonstrate Altered Physician Prescribing Behavior and Improved Patient Outcomes.

INTRODUCTION: This randomized, prospective study (MATCH) was designed to assess the clinical utility of a machine learning-based tool (Mind.Px) that p...

Predicting treatment outcome in congenital adrenal hyperplasia using urine steroidomics and machine learning.

OBJECTIVE: Treatment monitoring of individuals with congenital adrenal hyperplasia (CAH) remains unsatisfactory. Comprehensive 24 h urine steroid prof...

Comprehensive Characterization of Antidepressant Pharmacogenetics: A Systematic Review of Studies in Major Depressive Disorder.

Pharmacogenetics is a promising strategy to facilitate individualized care for patients with Major Depressive Disorder (MDD). Research is ongoing to i...