AIMC Topic: Software

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Deep learning-based mixed-dimensional Gaussian mixture model for characterizing variability in cryo-EM.

Nature methods
Structural flexibility and/or dynamic interactions with other molecules is a critical aspect of protein function. Cryogenic electron microscopy (cryo-EM) provides direct visualization of individual macromolecules sampling different conformational and...

Dialysis adequacy predictions using a machine learning method.

Scientific reports
Dialysis adequacy is an important survival indicator in patients with chronic hemodialysis. However, there are inconveniences and disadvantages to measuring dialysis adequacy by blood samples. This study used machine learning models to predict dialys...

Improving protein tertiary structure prediction by deep learning and distance prediction in CASP14.

Proteins
Substantial progresses in protein structure prediction have been made by utilizing deep-learning and residue-residue distance prediction since CASP13. Inspired by the advances, we improve our CASP14 MULTICOM protein structure prediction system by inc...

Platform for Healthcare Promotion and Cardiovascular Disease Prevention.

IEEE journal of biomedical and health informatics
This article presents the hardware-software design and implementation of an open, integrated, and scalable healthcare platform oriented to multiple point-care scenarios for healthcare promotion and cardiovascular disease prevention. The platform has ...

DDosTC: A Transformer-Based Network Attack Detection Hybrid Mechanism in SDN.

Sensors (Basel, Switzerland)
Software-defined networking (SDN) has emerged in recent years as a form of Internet architecture. Its scalability, dynamics, and programmability simplify the traditional Internet structure. This architecture realizes centralized management by separat...

Intelligent Network Applications Monitoring and Diagnosis Employing Software Sensing and Machine Learning Solutions.

Sensors (Basel, Switzerland)
The article presents a research in the field of complex sensing, detection, and recovery of communications networks applications and hardware, in case of failures, maloperations, or unauthorized intrusions. A case study, based on Davis AI engine oper...

Automated machine learning optimizes and accelerates predictive modeling from COVID-19 high throughput datasets.

Scientific reports
COVID-19 outbreak brings intense pressure on healthcare systems, with an urgent demand for effective diagnostic, prognostic and therapeutic procedures. Here, we employed Automated Machine Learning (AutoML) to analyze three publicly available high thr...

Supervised Learning of Neural Networks for Active Queue Management in the Internet.

Sensors (Basel, Switzerland)
The paper examines the AQM mechanism based on neural networks. The active queue management allows packets to be dropped from the router's queue before the buffer is full. The aim of the work is to use machine learning to create a model that copies th...

Learning the Fastest RNA Folding Path Based on Reinforcement Learning and Monte Carlo Tree Search.

Molecules (Basel, Switzerland)
RNA molecules participate in many important biological processes, and they need to fold into well-defined secondary and tertiary structures to realize their functions. Like the well-known protein folding problem, there is also an RNA folding problem....

Development of in-house fully residual deep convolutional neural network-based segmentation software for the male pelvic CT.

Radiation oncology (London, England)
BACKGROUND: This study aimed to (1) develop a fully residual deep convolutional neural network (CNN)-based segmentation software for computed tomography image segmentation of the male pelvic region and (2) demonstrate its efficiency in the male pelvi...