Inflammatory Bowel Disease

Deep learning approach to detection of colonoscopic information from unstructured reports.

BACKGROUND: Colorectal cancer is a leading cause of cancer deaths. Several screening tests, such as colonoscopy, can be used to find polyps or colorectal cancer. Colonoscopy reports are often written in unstructured narrative text. The information embedded in the reports can be used for various purposes, including colorectal cancer risk prediction, follow-up recommendation, and quality measurement...

Artificial Neural Network-Assisted Classification of Hearing Prognosis of Sudden Sensorineural Hearing Loss With Vertigo.

This study aimed to determine the impact on hearing prognosis of the coherent frequency with high magnitude-squared wavelet coherence (MSWC) in video head impulse test (vHIT) among patients with sudden sensorineural hearing loss with vertigo (SSNHLV) undergoing high-dose steroid treatment. This study was a retrospective cohort study. SSNHLV patients treated at our referral center from December 201...

Knowledge Sharing for Pulmonary Nodule Detection in Medical Cyber-Physical Systems.

With the rapid development of edge intelligence (EI) and machine learning (ML), the applications of Cyber-Physical Systems (CPS) have been discovered ...

Intraprocedure Artificial Intelligence Alert System for Colonoscopy Examination.

Colonoscopy is a valuable tool for preventing and reducing the incidence and mortality of colorectal cancer. Although several computer-aided colorecta...

Identification of Glucose Transport Modulators In Vitro and Method for Their Deep Learning Neural Network Behavioral Evaluation in Glucose Transporter 1-Deficient Mice.

Metabolic flux augmentation via glucose transport activation may be desirable in glucose transporter 1 (Glut1) deficiency syndrome (G1D) and dementia,...

Segment-then-Segment: Context-Preserving Crop-Based Segmentation for Large Biomedical Images.

Medical images are often of huge size, which presents a challenge in terms of memory requirements when training machine learning models. Commonly, the...

Inconsistent Partitioning and Unproductive Feature Associations Yield Idealized Radiomic Models.

Background Radiomics is the extraction of predefined mathematic features from medical images for the prediction of variables of clinical interest. Whi...

Artificial intelligence in cancer research and precision medicine: Applications, limitations and priorities to drive transformation in the delivery of equitable and unbiased care.

Artificial intelligence (AI) has experienced explosive growth in oncology and related specialties in recent years. The improved expertise in data capt...

Improving colorectal cancer screening - consumer-centred technological interventions to enhance engagement and participation amongst diverse cohorts.

The current "Gold Standard" colorectal cancer (CRC) screening approach of faecal occult blood test (FOBT) with follow-up colonoscopy has been shown to...

Computer-aided classification of colorectal segments during colonoscopy: a deep learning approach based on images of a magnetic endoscopic positioning device.

OBJECTIVE: Assessment of the anatomical colorectal segment of polyps during colonoscopy is important for treatment and follow-up strategies, but is la...

IBD: An Interpretable Backdoor-Detection Method via Multivariate Interactions.

Recent work has shown that deep neural networks are vulnerable to backdoor attacks. In comparison with the success of backdoor-attack methods, existin...

Molecular Networking and On-Tissue Chemical Derivatization for Enhanced Identification and Visualization of Steroid Glycosides by MALDI Mass Spectrometry Imaging.

Spatial metabolomics describes the spatially resolved analysis of interconnected pathways, biochemical reactions, and transport processes of small mol...

A novel application of neural networks to identify potentially effective combinations of biologic factors for enhancement of bone fusion/repair.

INTRODUCTION: The use of biologic adjuvants (orthobiologics) is becoming commonplace in orthopaedic surgery. Among other applications, biologics are o...

Artificial Intelligence and Deep Learning for Rheumatologists.

Deep learning has emerged as the leading method in machine learning, spawning a rapidly growing field of academic research and commercial applications...

Automated classification of estrous stage in rodents using deep learning.

The rodent estrous cycle modulates a range of biological functions, from gene expression to behavior. The cycle is typically divided into four stages,...

Robot-assisted laparoscopic surgery with a fluorescent near-infrared ray ureteral catheter for a rectal cancer patient with pelvic kidney: A case report.

An 85-year-old woman presented with a stomachache after a meal and was admitted to the previous clinic. Multi-detector computed tomography (CT) of the...

New endoscopic tools in inflammatory bowel disease.

Endoscopic remission is now considered the ultimate long-term goal for treating inflammatory bowel disease (IBD). Recent advances in endoscopic techni...

Deep learning-based automated quantification of goblet cell mucus using histological images as a predictor of clinical relapse of ulcerative colitis with endoscopic remission.

BACKGROUND: Mucin depletion is one of the histological indicators of clinical relapse among patients with ulcerative colitis (UC). Mucin depletion is ...

Deep Learning-Based Nuclear Morphometry Reveals an Independent Prognostic Factor in Mantle Cell Lymphoma.

Blastoid/pleomorphic morphology is associated with short survival in mantle cell lymphoma (MCL), but its prognostic value is overridden by Ki-67 in mu...

A Model of Normality Inspired Deep Learning Framework for Depression Relapse Prediction Using Audiovisual Data.

BACKGROUND: Depression (Major Depressive Disorder) is one of the most common mental illnesses. According to the World Health Organization, more than 3...