AIMC Topic: Deep Learning

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Artificial intelligence for disease diagnosis and risk prediction in nuclear cardiology.

Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology
Artificial intelligence (AI) techniques have emerged as a highly efficient approach to accurately and rapidly interpret diagnostic imaging and may play a vital role in nuclear cardiology. In nuclear cardiology, there are many clinical, stress, and im...

Registration-guided deep learning image segmentation for cone beam CT-based online adaptive radiotherapy.

Medical physics
PURPOSE: Adaptive radiotherapy (ART), especially online ART, effectively accounts for positioning errors and anatomical changes. One key component of online ART process is accurately and efficiently delineating organs at risk (OARs) and targets on on...

Benchmarking weakly-supervised deep learning pipelines for whole slide classification in computational pathology.

Medical image analysis
Artificial intelligence (AI) can extract visual information from histopathological slides and yield biological insight and clinical biomarkers. Whole slide images are cut into thousands of tiles and classification problems are often weakly-supervised...

Explainable artificial intelligence (XAI) in deep learning-based medical image analysis.

Medical image analysis
With an increase in deep learning-based methods, the call for explainability of such methods grows, especially in high-stakes decision making areas such as medical image analysis. This survey presents an overview of explainable artificial intelligenc...

Deep learning and the future of the Model for End-Stage Liver Disease-sodium score.

Liver transplantation : official publication of the American Association for the Study of Liver Diseases and the International Liver Transplantation Society

Deep-Learning-Assisted Stratification of Amyloid Beta Mutants Using Drying Droplet Patterns.

Advanced materials (Deerfield Beach, Fla.)
The development of simple and accurate methods to predict mutations in proteins remains an unsolved challenge in modern biochemistry. It is discovered that critical information about primary and secondary peptide structures can be inferred from the s...

Malignant Bone Tumors Diagnosis Using Magnetic Resonance Imaging Based on Deep Learning Algorithms.

Medicina (Kaunas, Lithuania)
: Malignant bone tumors represent a major problem due to their aggressiveness and low survival rate. One of the determining factors for improving vital and functional prognosis is the shortening of the time between the onset of symptoms and the momen...

Progressive compressive sensing of large images with multiscale deep learning reconstruction.

Scientific reports
Compressive sensing (CS) is a sub-Nyquist sampling framework that has been employed to improve the performance of numerous imaging applications during the last 15 years. Yet, its application for large and high-resolution imaging remains challenging i...

DLSSAffinity: protein-ligand binding affinity prediction a deep learning model.

Physical chemistry chemical physics : PCCP
Evaluating the protein-ligand binding affinity is a substantial part of the computer-aided drug discovery process. Most of the proposed computational methods predict protein-ligand binding affinity using either limited full-length protein 3D structur...