AIMC Topic: Algorithms

Clear Filters Showing 3151 to 3160 of 28713 articles

Deep learning based screening model for hip diseases on plain radiographs.

PloS one
INTRODUCTION: The interpretation of plain hip radiographs can vary widely among physicians. This study aimed to develop and validate a deep learning-based screening model for distinguishing normal hips from severe hip diseases on plain radiographs.

Predicting software reuse using machine learning techniques-A case study on open-source Java software systems.

PloS one
Software reuse is an essential practice to increase efficiency and reduce costs in software production. Software reuse practices range from reusing artifacts, libraries, components, packages, and APIs. Identifying suitable software for reuse requires...

Image captioning in Bengali language using visual attention.

PloS one
Automatically generating image captions poses one of the most challenging applications within artificial intelligence due to its integration of computer vision and natural language processing algorithms. This task becomes notably more formidable when...

ILR-Net: Low-light image enhancement network based on the combination of iterative learning mechanism and Retinex theory.

PloS one
Images captured in nighttime or low-light environments are often affected by external factors such as noise and lighting. Aiming at the existing image enhancement algorithms tend to overly focus on increasing brightness, while neglecting the enhancem...

Multi-step depth enhancement refine network with multi-view stereo.

PloS one
This paper introduces an innovative multi-view stereo matching network-the Multi-Step Depth Enhancement Refine Network (MSDER-MVS), aimed at improving the accuracy and computational efficiency of high-resolution 3D reconstruction. The MSDER-MVS netwo...

Cost-sensitive multi-kernel ELM based on reduced expectation kernel auto-encoder.

PloS one
ELM (Extreme learning machine) has drawn great attention due its high training speed and outstanding generalization performance. To solve the problem that the long training time of kernel ELM auto-encoder and the difficult setting of the weight of ke...

Optimising test intervals for individuals with type 2 diabetes: A machine learning approach.

PloS one
BACKGROUND: Chronic disease monitoring programs often adopt a one-size-fits-all approach that does not consider variation in need, potentially leading to excessive or insufficient support for patients at different risk levels. Machine learning (ML) d...

Vertical federated learning based on data subset representation for healthcare application.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Artificial intelligence is increasingly essential for disease classification and clinical diagnosis tasks in healthcare. Given the strict privacy needs of healthcare data, Vertical Federated Learning (VFL) has been introduce...

FakET: Simulating cryo-electron tomograms with neural style transfer.

Structure (London, England : 1993)
In cryo-electron microscopy, accurate particle localization and classification are imperative. Recent deep learning solutions, though successful, require extensive training datasets. The protracted generation time of physics-based models, often emplo...

Neuradicon: Operational representation learning of neuroimaging reports.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Radiological reports typically summarize the content and interpretation of imaging studies in unstructured form that precludes quantitative analysis. This limits the monitoring of radiological services to throughput undiffer...