AIMC Topic: Algorithms

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A deep learning-based automated algorithm for labeling coronary arteries in computed tomography angiography images.

BMC medical informatics and decision making
OBJECTIVE: Using two three-dimensional U-Net architectures for myocardium structure extraction and a distance transformation algorithm specifically for the left circumflex artery, we have designed a fully automated algorithm for coronary artery label...

CT scan pancreatic cancer segmentation and classification using deep learning and the tunicate swarm algorithm.

PloS one
Pancreatic cancer (PC) is a very lethal disease with a low survival rate, making timely and accurate diagnoses critical for successful treatment. PC classification in computed tomography (CT) scans is a vital task that aims to accurately discriminate...

Framework for Radiation Oncology Department-wide Evaluation and Implementation of Commercial Artificial Intelligence Autocontouring.

Practical radiation oncology
PURPOSE: Artificial intelligence (AI)-based autocontouring in radiation oncology has potential benefits such as standardization and time savings. However, commercial AI solutions require careful evaluation before clinical integration. We developed a ...

Artificial intelligence: Machine learning approach for screening large database and drug discovery.

Antiviral research
Recent research in drug discovery dealing with many faces difficulties, including development of new drugs during disease outbreak and drug resistance due to rapidly accumulating mutations. Virtual screening is the most widely used method in computer...

Predicting dengue transmission rates by comparing different machine learning models with vector indices and meteorological data.

Scientific reports
Machine learning algorithms (ML) are receiving a lot of attention in the development of predictive models for monitoring dengue transmission rates. Previous work has focused only on specific weather variables and algorithms, and there is still a need...

Low-variance Forward Gradients using Direct Feedback Alignment and momentum.

Neural networks : the official journal of the International Neural Network Society
Supervised learning in deep neural networks is commonly performed using error backpropagation. However, the sequential propagation of errors during the backward pass limits its scalability and applicability to low-powered neuromorphic hardware. There...

An edge-device-compatible algorithm for valvular heart diseases screening using phonocardiogram signals with a lightweight convolutional neural network and self-supervised learning.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVES: Detection and classification of heart murmur using mobile-phone-collected sound is an emerging approach to the scale-up screening of valvular heart disease at a population level. Nonetheless, the widespread adoption of arti...

Leveraging attention-enhanced variational autoencoders: Novel approach for investigating latent space of aptamer sequences.

International journal of biological macromolecules
Aptamers are increasingly recognized as potent alternatives to antibodies for diagnostic and therapeutic applications. The application of deep learning, particularly attention-based models, for aptamer (DNA/RNA) sequences is an innovative field. The ...

Multi-stakeholder preferences for the use of artificial intelligence in healthcare: A systematic review and thematic analysis.

Social science & medicine (1982)
INTRODUCTION: Despite the proliferation of Artificial Intelligence (AI) technology over the last decade, clinician, patient, and public perceptions of its use in healthcare raise a number of ethical, legal and social questions. We systematically revi...