AIMC Topic: Algorithms

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STAIG: Spatial transcriptomics analysis via image-aided graph contrastive learning for domain exploration and alignment-free integration.

Nature communications
Spatial transcriptomics is an essential application for investigating cellular structures and interactions and requires multimodal information to precisely study spatial domains. Here, we propose STAIG, a deep-learning model that integrates gene expr...

The Application of Machine Learning Algorithms to Predict HIV Testing in Repeated Adult Population-Based Surveys in South Africa: Protocol for a Multiwave Cross-Sectional Analysis.

JMIR research protocols
BACKGROUND: HIV testing is the cornerstone of HIV prevention and a pivotal step in realizing the Joint United Nations Program on HIV/AIDS (UNAIDS) goal of ending AIDS by 2030. Despite the availability of relevant survey data, there exists a research ...

Intelligent classification of computer vulnerabilities and network security management system: Combining memristor neural network and improved TCNN model.

PloS one
To enhance the intelligent classification of computer vulnerabilities and improve the efficiency and accuracy of network security management, this study delves into the application of a comprehensive classification system that integrates the Memristo...

Distributed Denial of Services (DDoS) attack detection in SDN using Optimizer-equipped CNN-MLP.

PloS one
Software-Defined Networks (SDN) provides more control and network operation over a network infrastructure as an emerging and revolutionary paradigm in networking. Operating the many network applications and preserving the network services and functio...

Enhanced ResNet-50 for garbage classification: Feature fusion and depth-separable convolutions.

PloS one
As people's material living standards continue to improve, the types and quantities of household garbage they generate rapidly increase. Therefore, it is urgent to develop a reasonable and effective method for garbage classification. This is importan...

Classification of CT scan and X-ray dataset based on deep learning and particle swarm optimization.

PloS one
In 2019, the novel coronavirus swept the world, exposing the monitoring and early warning problems of the medical system. Computer-aided diagnosis models based on deep learning have good universality and can well alleviate these problems. However, tr...

A safe-enhanced fully closed-loop artificial pancreas controller based on deep reinforcement learning.

PloS one
Patients with type 1 diabetes and their physicians have long desired a fully closed-loop artificial pancreas (AP) system that can alleviate the burden of blood glucose regulation. Although deep reinforcement learning (DRL) methods theoretically enabl...

Convolutional neural network-based method for the real-time detection of reflex syncope during head-up tilt test.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVES: Reflex syncope (RS) is the most common type of syncope caused by dysregulation of the autonomic nervous system. Diagnosing RS typically involves the head-up tilt test (HUTT), which tracks physiological signals such as blood...

Automated spinopelvic measurements on radiographs with artificial intelligence: a multi-reader study.

La Radiologia medica
PURPOSE: To develop an artificial intelligence (AI) algorithm for automated measurements of spinopelvic parameters on lateral radiographs and compare its performance to multiple experienced radiologists and surgeons.

A multiscale molecular structural neural network for molecular property prediction.

Molecular diversity
Molecular Property Prediction (MPP) is a fundamental task in important research fields such as chemistry, materials, biology, and medicine, where traditional computational chemistry methods based on quantum mechanics often consume substantial time an...