AIMC Topic: Algorithms

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A Closed-Loop Method for Multiperiod Intelligent Information Processing with Cost Constraints under the Fuzzy Environment.

Computational intelligence and neuroscience
From trivial matters in life to major scientific projects related to the fate of mankind, decision-making is everywhere. Whether high-quality decisions can be made often directly affects the development of affairs, especially when sudden disasters oc...

Diagnostic Assessment of Deep Learning Algorithms for Frozen Tissue Section Analysis in Women with Breast Cancer.

Cancer research and treatment
PURPOSE: Assessing the metastasis status of the sentinel lymph nodes (SLNs) for hematoxylin and eosin-stained frozen tissue sections by pathologists is an essential but tedious and time-consuming task that contributes to accurate breast cancer stagin...

A multi-scale evolutionary deep learning model based on CEEMDAN, improved whale optimization algorithm, regularized extreme learning machine and LSTM for AQI prediction.

Environmental research
With the rapid development of economy, air pollution occurs frequently, which has a huge negative impact on human health and urban ecosystem. Air quality index (AQI) can directly reflect the degree of air pollution. Accurate AQI trend prediction can ...

Femoral image segmentation based on two-stage convolutional network using 3D-DMFNet and 3D-ResUnet.

Computer methods and programs in biomedicine
OBJECTIVE: The femur is a typical human long bone with an irregular spatial structure. Femoral fractures are the most common occurrence in middle-aged and older adults. The structure of human bone tissue is very complex, and there are significant dif...

Imbalanced low-rank tensor completion via latent matrix factorization.

Neural networks : the official journal of the International Neural Network Society
Tensor completion has been widely used in computer vision and machine learning. Most existing tensor completion methods empirically assume the intrinsic tensor is simultaneous low-rank in all over modes. However, tensor data recorded from real-world ...

Plant-scale biogas production prediction based on multiple hybrid machine learning technique.

Bioresource technology
The parameters from full-scale biogas plants are highly nonlinear and imbalanced, resulting in low prediction accuracy when using traditional machine learning algorithms. In this study, a hybrid extreme learning machine (ELM) model was proposed to im...

Where Nanosensors Meet Machine Learning: Prospects and Challenges in Detecting Disease X.

ACS nano
Disease X is a hypothetical unknown disease that has the potential to cause an epidemic or pandemic outbreak in the future. Nanosensors are attractive portable devices that can swiftly screen disease biomarkers on site, reducing the reliance on labor...

Comparing machine learning algorithms to predict 5-year survival in patients with chronic myeloid leukemia.

BMC medical informatics and decision making
INTRODUCTION: Chronic myeloid leukemia (CML) is a myeloproliferative disorder resulting from the translocation of chromosomes 19 and 22. CML includes 15-20% of all cases of leukemia. Although bone marrow transplant and, more recently, tyrosine kinase...

A novel optimized tiny YOLOv3 algorithm for the identification of objects in the lawn environment.

Scientific reports
Based on the problem of insufficient accuracy of the original tiny YOLOv3 algorithm for object detection in a lawn environment, an Optimized tiny YOLOv3 algorithm with less computation and higher accuracy is proposed. Three reasons affect the accurac...

Effectiveness Assessment of College Ideological and Political Courses Using BP Neural Networks in Network Environment.

Journal of environmental and public health
We will not be able to provide educators with the assistance they require to implement the network IPECU and boost the effectiveness of the network IPE until we have established a trustworthy and effective assessment system. By first identifying the ...