AIMC Topic: Prospective Studies

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Remotely Controlled Mandibular Positioning During Drug-Induced Sleep Endoscopy Toward Mandibular Advancement Device Therapy: Feasibility and Protocol.

Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine
STUDY OBJECTIVES: The potential of a remotely controlled mandibular positioner (RCMP) during sleep studies in individual patients suffering from obstructive sleep apnea (OSA) for the determination of the effective target protrusive position (ETPP) of...

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

Annals of internal medicine
BACKGROUND: Computer-aided diagnosis (CAD) for colonoscopy may help endoscopists distinguish neoplastic polyps (adenomas) requiring resection from nonneoplastic polyps not requiring resection, potentially reducing cost.

Automated classification of osteomeatal complex inflammation on computed tomography using convolutional neural networks.

International forum of allergy & rhinology
BACKGROUND: Convolutional neural networks (CNNs) are advanced artificial intelligence algorithms well suited to image classification tasks with variable features. These have been used to great effect in various real-world applications including handw...

Robot-assisted Kidney Autotransplantation: A Minimally Invasive Way to Salvage Kidneys.

European urology focus
BACKGROUND: Kidney autotransplantation (KAT) is the ultimate way to salvage kidneys with complex renovascular, ureteral, or malignant pathologies that are not amenable to in situ reconstruction. A minimally invasive approach could broaden its adoptio...

Improved perfusion pattern score association with type 2 diabetes severity using machine learning pipeline: Pilot study.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: Type 2 diabetes mellitus (T2DM) is associated with alterations in the blood-brain barrier, neuronal damage, and arterial stiffness, thus affecting cerebral metabolism and perfusion. There is a need to implement machine-learning methodolog...

Hybrid 3D/2D Convolutional Neural Network for Hemorrhage Evaluation on Head CT.

AJNR. American journal of neuroradiology
BACKGROUND AND PURPOSE: Convolutional neural networks are a powerful technology for image recognition. This study evaluates a convolutional neural network optimized for the detection and quantification of intraparenchymal, epidural/subdural, and suba...

Use of Machine Learning on Contact Lens Sensor-Derived Parameters for the Diagnosis of Primary Open-angle Glaucoma.

American journal of ophthalmology
PURPOSE: To test the hypothesis that contact lens sensor (CLS)-based 24-hour profiles of ocular volume changes contain information complementary to intraocular pressure (IOP) to discriminate between primary open-angle glaucoma (POAG) and healthy (H) ...

A machine-learning framework for automatic reference-free quality assessment in MRI.

Magnetic resonance imaging
Magnetic resonance (MR) imaging offers a wide variety of imaging techniques. A large amount of data is created per examination which needs to be checked for sufficient quality in order to derive a meaningful diagnosis. This is a manual process and th...

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

The journal of maternal-fetal & neonatal medicine : the official journal of the European Association of Perinatal Medicine, the Federation of Asia and Oceania Perinatal Societies, the International Society of Perinatal Obstetricians
A large recent study analyzed the relationship between multiple factors and neonatal outcome and in preterm births. Study variables included the reason for admission, indication for delivery, optimal steroid use, gestational age, and other potential...