AIMC Topic: Deep Learning

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Predicting pregnancy status from mid-infrared spectroscopy in dairy cow milk using deep learning.

Journal of dairy science
Accurately identifying pregnancy status is imperative for a profitable dairy enterprise. Mid-infrared (MIR) spectroscopy is routinely used to determine fat and protein concentrations in milk samples. Mid-infrared spectra have successfully been used t...

Review of deep learning algorithms for the automatic detection of intracranial hemorrhages on computed tomography head imaging.

Journal of neurointerventional surgery
Artificial intelligence is a rapidly evolving field, with modern technological advances and the growth of electronic health data opening new possibilities in diagnostic radiology. In recent years, the performance of deep learning (DL) algorithms on v...

An Automated Deep Learning Method for Tile AO/OTA Pelvic Fracture Severity Grading from Trauma whole-Body CT.

Journal of digital imaging
Admission trauma whole-body CT is routinely employed as a first-line diagnostic tool for characterizing pelvic fracture severity. Tile AO/OTA grade based on the presence or absence of rotational and translational instability corresponds with need for...

A combined convolutional and recurrent neural network for enhanced glaucoma detection.

Scientific reports
Glaucoma, a leading cause of blindness, is a multifaceted disease with several patho-physiological features manifesting in single fundus images (e.g., optic nerve cupping) as well as fundus videos (e.g., vascular pulsatility index). Current convoluti...

Deep learning based prediction of extraction difficulty for mandibular third molars.

Scientific reports
This paper proposes a convolutional neural network (CNN)-based deep learning model for predicting the difficulty of extracting a mandibular third molar using a panoramic radiographic image. The applied dataset includes a total of 1053 mandibular thir...

Deep learning predicts postsurgical recurrence of hepatocellular carcinoma from digital histopathologic images.

Scientific reports
Recurrence risk stratification of patients undergoing primary surgical resection for hepatocellular carcinoma (HCC) is an area of active investigation, and several staging systems have been proposed to optimize treatment strategies. However, as many ...

A deep learning based framework for the registration of three dimensional multi-modal medical images of the head.

Scientific reports
Image registration is a fundamental task in image analysis in which the transform that moves the coordinate system of one image to another is calculated. Registration of multi-modal medical images has important implications for clinical diagnosis, tr...

Deep learning-based detection of dental prostheses and restorations.

Scientific reports
The purpose of this study is to develop a method for recognizing dental prostheses and restorations of teeth using a deep learning. A dataset of 1904 oral photographic images of dental arches (maxilla: 1084 images; mandible: 820 images) was used in t...

MVP predicts the pathogenicity of missense variants by deep learning.

Nature communications
Accurate pathogenicity prediction of missense variants is critically important in genetic studies and clinical diagnosis. Previously published prediction methods have facilitated the interpretation of missense variants but have limited performance. H...

Saliency Prediction on Omnidirectional Image With Generative Adversarial Imitation Learning.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
When watching omnidirectional images (ODIs), subjects can access different viewports by moving their heads. Therefore, it is necessary to predict subjects' head fixations on ODIs. Inspired by generative adversarial imitation learning (GAIL), this pap...