AIMC Topic: Humans

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Deep Learning Reconstruction of Prospectively Accelerated MRI of the Pancreas: Clinical Evaluation of Shortened Breath-Hold Examinations With Dixon Fat Suppression.

Investigative radiology
OBJECTIVE: Deep learning (DL)-enabled magnetic resonance imaging (MRI) reconstructions can enable shortening of breath-hold examinations and improve image quality by reducing motion artifacts. Prospective studies with DL reconstructions of accelerate...

In silico method and bioactivity evaluation to discover novel antimicrobial agents targeting FtsZ protein: Machine learning, virtual screening and antibacterial mechanism study.

Naunyn-Schmiedeberg's archives of pharmacology
This research paper utilizes a fused-in-silico approach alongside bioactivity evaluation to identify active FtsZ inhibitors for drug discovery. Initially, ROC-guided machine learning was employed to obtain almost 13182 compounds from three libraries....

Machine learning-enhanced HRCT analysis for diagnosis and severity assessment in pediatric asthma.

Pediatric pulmonology
OBJECTIVES: Chest high-resolution computed tomography (HRCT) is conditionally recommended to rule out conditions that mimic or coexist with severe asthma in children. However, it may provide valuable insights into identifying structural airway change...

HDConv: Heterogeneous kernel-based dilated convolutions.

Neural networks : the official journal of the International Neural Network Society
Dilated convolution has been widely used in various computer vision tasks due to its ability to expand the receptive field while maintaining the resolution of feature maps. However, the critical challenge is the gridding problem caused by the isomorp...

Characterizing sector-oriented roadside exposure to ultrafine particles (PM) via machine learning models: Implications of covariates influences on sectors variability.

Environmental pollution (Barking, Essex : 1987)
Ultrafine particles (UFPs; PM) possess intensified health risk due to their smaller size and unique spatial variability. One of major emission sources for UFPs is vehicle exhaust, which varies based on the traffic composition in each type of roadside...

Machine learning in the prediction of treatment response in rheumatoid arthritis: A systematic review.

Seminars in arthritis and rheumatism
OBJECTIVE: This study aimed to investigate the current status and performance of machine learning (ML) approaches in providing reproducible treatment response predictions.

Noninvasive and fast method of calculation for instantaneous wave-free ratio based on haemodynamics and deep learning.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVES: Instantaneous wave-free ratio (iFR) is a new invasive indicator of myocardial ischaemia, and its diagnostic performance is as good as the "gold standard" of myocardial ischaemia diagnosis: fractional flow reserve (FFR). iFR...

The Application of Artificial Intelligence to Acoustic Data in Otolaryngology.

Otolaryngologic clinics of North America
Artificial intelligence (AI), particularly deep learning, has revolutionized various fields through its ability to model complex, noisy systems with high accuracy. Driven by advancements in deep neural networks (DNNs), hardware, and data digitization...

Detection and characterization of pancreatic lesion with artificial intelligence: The SFR 2023 artificial intelligence data challenge.

Diagnostic and interventional imaging
PURPOSE: The purpose of the 2023 SFR data challenge was to invite researchers to develop artificial intelligence (AI) models to identify the presence of a pancreatic mass and distinguish between benign and malignant pancreatic masses on abdominal com...