AIMC Topic: Deep Learning

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Augmented deep learning model for improved quantitative accuracy of MR-based PET attenuation correction in PSMA PET-MRI prostate imaging.

European journal of nuclear medicine and molecular imaging
PURPOSE: Estimation of accurate attenuation maps for whole-body positron emission tomography (PET) imaging in simultaneous PET-MRI systems is a challenging problem as it affects the quantitative nature of the modality. In this study, we aimed to impr...

PopPhy-CNN: A Phylogenetic Tree Embedded Architecture for Convolutional Neural Networks to Predict Host Phenotype From Metagenomic Data.

IEEE journal of biomedical and health informatics
Accurate prediction of the host phenotype from a metagenomic sample and identification of the associated microbial markers are important in understanding potential host-microbiome interactions related to disease initiation and progression. We introdu...

Deep learning-based classification of rectal fecal retention and analysis of fecal properties using ultrasound images in older adult patients.

Japan journal of nursing science : JJNS
AIM: The present study aimed to analyze the use of machine learning in ultrasound (US)-based fecal retention assessment.

Novel artificial intelligence system increases the detection of prostate cancer in whole slide images of core needle biopsies.

Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc
Prostate cancer (PrCa) is the second most common cancer among men in the United States. The gold standard for detecting PrCa is the examination of prostate needle core biopsies. Diagnosis can be challenging, especially for small, well-differentiated ...

Multi-feature fusion for deep learning to predict plant lncRNA-protein interaction.

Genomics
Long non-coding RNAs (lncRNAs) play key roles in regulating cellular biological processes through diverse molecular mechanisms including binding to RNA binding proteins. The majority of plant lncRNAs are functionally uncharacterized, thus, accurate p...

Deep learning-based fully automatic segmentation of wrist cartilage in MR images.

NMR in biomedicine
The study objective was to investigate the performance of a dedicated convolutional neural network (CNN) optimized for wrist cartilage segmentation from 2D MR images. CNN utilized a planar architecture and patch-based (PB) training approach that ensu...

Development of a real-time indoor location system using bluetooth low energy technology and deep learning to facilitate clinical applications.

Medical physics
PURPOSE: An indoor, real-time location system (RTLS) can benefit both hospitals and patients by improving clinical efficiency through data-driven optimization of procedures. Bluetooth-based RTLS systems are cost-effective but lack accuracy because Bl...

Artificial intelligence radiogenomics for advancing precision and effectiveness in oncologic care (Review).

International journal of oncology
The new era of artificial intelligence (AI) has introduced revolutionary data‑driven analysis paradigms that have led to significant advancements in information processing techniques in the context of clinical decision‑support systems. These advances...

Trajectory-level fog detection based on in-vehicle video camera with TensorFlow deep learning utilizing SHRP2 naturalistic driving data.

Accident; analysis and prevention
Providing drivers with real-time weather information and driving assistance during adverse weather, including fog, is crucial for safe driving. The primary focus of this study was to develop an affordable in-vehicle fog detection method, which will p...