Inflammatory Bowel Disease

Prediction of findings at screening colonoscopy using a machine learning algorithm based on complete blood counts (ColonFlag).

Adenomatous polyps are a common precursor lesion for colorectal cancer. ColonFlag is a machine- lear...

Level of circulating steroid hormones in malaria and cutaneous leishmaniasis: a case control study.

Epidemiological and clinical studies have shown a great difference in the severity and prevalence of...

Predicting the naturalistic course of depression from a wide range of clinical, psychological, and biological data: a machine learning approach.

Many variables have been linked to different course trajectories of depression. These findings, howe...

Human-machine collaboration: bringing artificial intelligence into colonoscopy.

Development and validation of a deep-learning algorithm for the detection of polyps during colonoscopy.

The detection and removal of precancerous polyps via colonoscopy is the gold standard for the preven...

Real-Time Use of Artificial Intelligence in Identification of Diminutive Polyps During Colonoscopy: A Prospective Study.

BACKGROUND: Computer-aided diagnosis (CAD) for colonoscopy may help endoscopists distinguish neoplas...

Using Machine Learning to Aid the Interpretation of Urine Steroid Profiles.

BACKGROUND: Urine steroid profiles are used in clinical practice for the diagnosis and monitoring of...

Estimating risk of severe neonatal morbidity in preterm births under 32 weeks of gestation.

A large recent study analyzed the relationship between multiple factors and neonatal outcome and in...

Preparation of Molecularly Imprinted Microspheres as Biomimetic Recognition Material for In Situ Adsorption and Selective Chemiluminescence Determination of Bisphenol A.

Bisphenol A (BPA) is an endocrine disrupter in environments which can induce abnormal differentiatio...

Deep Learning Localizes and Identifies Polyps in Real Time With 96% Accuracy in Screening Colonoscopy.

BACKGROUND & AIMS: The benefit of colonoscopy for colorectal cancer prevention depends on the adenom...

Deep learning and conditional random fields-based depth estimation and topographical reconstruction from conventional endoscopy.

Colorectal cancer is the fourth leading cause of cancer deaths worldwide and the second leading caus...

Predictive modeling of treatment resistant depression using data from STAR*D and an independent clinical study.

Identification of risk factors of treatment resistance may be useful to guide treatment selection, a...

Plasminogen activator inhibitor-1 is associated with the metabolism and development of advanced colonic polyps.

Implications of plasminogen activator inhibitor-1 (PAI-1) in colonic polyps remain elusive. A prospe...

Modeling asynchronous event sequences with RNNs.

Sequences of events have often been modeled with computational techniques, but typical preprocessing...

Unsupervised Reverse Domain Adaptation for Synthetic Medical Images via Adversarial Training.

To realize the full potential of deep learning for medical imaging, large annotated datasets are req...

Evaluation of Natural Language Processing (NLP) systems to annotate drug product labeling with MedDRA terminology.

INTRODUCTION: The FDA Adverse Event Reporting System (FAERS) is a primary data source for identifyin...

Vitamin D Deficiency in a Portuguese Cohort of Patients with Inflammatory Bowel Disease: Prevalence and Relation to Disease Activity.

BACKGROUND AND AIMS: Vitamin D deficiency is more common in inflammatory bowel disease (IBD) patient...

Machine learning identifies signatures of host adaptation in the bacterial pathogen Salmonella enterica.

Emerging pathogens are a major threat to public health, however understanding how pathogens adapt to...

Natural Language Processing Accurately Calculates Adenoma and Sessile Serrated Polyp Detection Rates.

BACKGROUND: ADR is a widely used colonoscopy quality indicator. Calculation of ADR is labor-intensiv...

Effect of dilution in asymmetric recurrent neural networks.

We study with numerical simulation the possible limit behaviors of synchronous discrete-time determi...

Artificial Intelligence-Assisted Polyp Detection for Colonoscopy: Initial Experience.