AIMC Topic: Deep Learning

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Deep-learning-based prognostic modeling for incident heart failure in patients with diabetes using electronic health records: A retrospective cohort study.

PloS one
Patients with type 2 diabetes mellitus (T2DM) have more than twice the risk of developing heart failure (HF) compared to patients without diabetes. The present study is aimed to build an artificial intelligence (AI) prognostic model that takes in acc...

Automatic Detection of Peripheral Retinal Lesions From Ultrawide-Field Fundus Images Using Deep Learning.

Asia-Pacific journal of ophthalmology (Philadelphia, Pa.)
PURPOSE: To establish a multilabel-based deep learning (DL) algorithm for automatic detection and categorization of clinically significant peripheral retinal lesions using ultrawide-field fundus images.

Deep Learning Approach for MRI in the Classification of Anterior Talofibular Ligament Injuries.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: Diagnosing anterior talofibular ligament (ATFL) injuries differs among radiologists. Further assessment of ATFL tears is valuable for clinical decision-making.

Artificial Intelligence in Nuclear Cardiology.

Cardiology clinics
Artificial intelligence (AI) encompasses a variety of computer algorithms that have a wide range of potential clinical applications in nuclear cardiology. This article will introduce core terminology and concepts for AI including classifications of A...

A study of transfer of information in animal collectives using deep learning tools.

Philosophical transactions of the Royal Society of London. Series B, Biological sciences
We studied how the interactions among animals in a collective allow for the transfer of information. We performed laboratory experiments to study how zebrafish in a collective follow a subset of trained animals that move towards a light when it turns...

Sinogram domain metal artifact correction of CT via deep learning.

Computers in biology and medicine
PURPOSE: Metal artifacts can significantly decrease the quality of computed tomography (CT) images. This occurs as X-rays penetrate implanted metals, causing severe attenuation and resulting in metal artifacts in the CT images. This degradation in im...

New Cognitive Deep-Learning CAPTCHA.

Sensors (Basel, Switzerland)
CAPTCHA (Completely Automated Public Turing test to tell Computers and Humans Apart), or HIP (Human Interactive Proof), has long been utilized to avoid bots manipulating web services. Over the years, various CAPTCHAs have been presented, primarily to...

Deep learning ensemble 2D CNN approach towards the detection of lung cancer.

Scientific reports
In recent times, deep learning has emerged as a great resource to help research in medical sciences. A lot of work has been done with the help of computer science to expose and predict different diseases in human beings. This research uses the Deep L...

Low-data interpretable deep learning prediction of antibody viscosity using a biophysically meaningful representation.

Scientific reports
Deep learning, aided by the availability of big data sets, has led to substantial advances across many disciplines. However, many scientific problems of practical interest lack sufficiently large datasets amenable to deep learning. Prediction of anti...

Deep learning based automatic contour refinement for inaccurate auto-segmentation in MR-guided adaptive radiotherapy.

Physics in medicine and biology
Fast and accurate auto-segmentation is essential for magnetic resonance-guided adaptive radiation therapy (MRgART). Deep learning auto-segmentation (DLAS) is not always clinically acceptable, particularly for complex abdominal organs. We previously r...