AIMC Topic: Double-Blind Method

Clear Filters Showing 41 to 50 of 145 articles

An Artificial-Intelligence-Discovered Functional Ingredient, NRT_N0G5IJ, Derived from , Decreases HbA1c in a Prediabetic Population.

Nutrients
The prevalence of prediabetes is rapidly increasing, and this can lead to an increased risk for individuals to develop type 2 diabetes and associated diseases. Therefore, it is necessary to develop nutritional strategies to maintain healthy glucose l...

The Influence of Fluid Intake Behavior on Cognition and Mood among College Students in Baoding, China.

Annals of nutrition & metabolism
INTRODUCTION: Water is a critical nutrient, and it is important for the maintenance of the physiological function of the human body [1-3]. In addition to fluid amounts, f...

Effect of Machine Learning on Dispatcher Recognition of Out-of-Hospital Cardiac Arrest During Calls to Emergency Medical Services: A Randomized Clinical Trial.

JAMA network open
IMPORTANCE: Emergency medical dispatchers fail to identify approximately 25% of cases of out-of-hospital cardiac arrest (OHCA), resulting in lost opportunities to save lives by initiating cardiopulmonary resuscitation.

Tualang honey versus steroid impregnated nasal dressing following endoscopic sinus surgery: a randomized controlled trial.

Journal of complementary & integrative medicine
OBJECTIVES: Recurrence rate of nasal polyps is high following endoscopic sinus surgery. To improve the surgical outcome, steroid impregnated nasal dressing is used postoperatively We aimed to compare the effect of Tualang honey impregnated nasal dres...

Characterization of specific and distinct patient types in clinical trials of acute schizophrenia using an uncorrelated PANSS score matrix transform (UPSM).

Psychiatry research
Understanding the specificity of symptom change in schizophrenia can facilitate the evaluation antipsychotic efficacy for different symptom domains. Previous work identified a transform of PANSS using an uncorrelated PANSS score matrix (UPSM) to redu...

OCT Signal Enhancement with Deep Learning.

Ophthalmology. Glaucoma
PURPOSE: To establish whether deep learning methods are able to improve the signal-to-noise ratio of time-domain (TD) OCT images to approach that of spectral-domain (SD) OCT images.

Machine learning and individual variability in electric field characteristics predict tDCS treatment response.

Brain stimulation
BACKGROUND: Transcranial direct current stimulation (tDCS) is widely investigated as a therapeutic tool to enhance cognitive function in older adults with and without neurodegenerative disease. Prior research demonstrates that electric current delive...

Effect of a deep-learning computer-aided detection system on adenoma detection during colonoscopy (CADe-DB trial): a double-blind randomised study.

The lancet. Gastroenterology & hepatology
BACKGROUND: Colonoscopy with computer-aided detection (CADe) has been shown in non-blinded trials to improve detection of colon polyps and adenomas by providing visual alarms during the procedure. We aimed to assess the effectiveness of a CADe system...