Inflammatory Bowel Disease

Development and Validation of Machine Learning Models in Prediction of Remission in Patients With Moderate to Severe Crohn Disease.

IMPORTANCE: Biological therapies have revolutionized inflammatory bowel disease management, but many...

Prediction of Hemolytic Toxicity for Saponins by Machine-Learning Methods.

Saponins are a type of compounds bearing a hydrophobic steroid/triterpenoid moiety and hydrophilic c...

Improving Automatic Polyp Detection Using CNN by Exploiting Temporal Dependency in Colonoscopy Video.

Automatic polyp detection has been shown to be difficult due to various polyp-like structures in the...

Quality assurance of computer-aided detection and diagnosis in colonoscopy.

Recent breakthroughs in artificial intelligence (AI), specifically via its emerging sub-field "deep ...

Predicting one-year outcome in first episode psychosis using machine learning.

BACKGROUND: Early illness course correlates with long-term outcome in psychosis. Accurate prediction...

Discovery of small molecule binders of human FSHR(TMD) with novel structural scaffolds by integrating structural bioinformatics and machine learning algorithms.

BACKGROUND: The activation of follicle stimulating hormone receptor (FSHR) by FSH and the consequent...

Addressing priority challenges in the detection and assessment of colorectal polyps from capsule endoscopy and colonoscopy in colorectal cancer screening using machine learning.

BACKGROUND: Colorectal capsule endoscopy (CCE) is a potentially valuable patient-friendly technique ...

Artificial intelligence and colonoscopy: Current status and future perspectives.

BACKGROUND AND AIM: Application of artificial intelligence in medicine is now attracting substantial...

Potential roles of artificial intelligence learning and faecal immunochemical testing for prioritisation of colonoscopy in anaemia.

Iron deficiency anaemia (IDA) is the most common cause of anaemia and a frequent indication for colo...

Effects of Progesterone and 17β-Estradiol under Presence or Absence of FBS on Plasminogen Activators Activity in Porcine Uterine Epithelial Cells.

The present study was conducted to investigate the regulatory mechanism of plasminogen activators (P...

Association of time to colonoscopy after a positive fecal test result and fecal hemoglobin concentration with risk of advanced colorectal neoplasia.

BACKGROUND: We evaluated the risk of advanced colorectal neoplasia (ACRN) and colorectal cancer (CRC...

Artificial intelligence and computer-aided diagnosis in colonoscopy: current evidence and future directions.

Computer-aided diagnosis offers a promising solution to reduce variation in colonoscopy performance....

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...