AIMC Topic: Algorithms

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Enhanced Watershed Segmentation Algorithm-Based Modified ResNet50 Model for Brain Tumor Detection.

BioMed research international
This work delivers a novel technique to detect brain tumor with the help of enhanced watershed modeling integrated with a modified ResNet50 architecture. It also involves stochastic approaches to help in developing enhanced watershed modeling. Cancer...

Artificial intelligence-based classification of bone tumors in the proximal femur on plain radiographs: System development and validation.

PloS one
PURPOSE: Early detection and classification of bone tumors in the proximal femur is crucial for their successful treatment. This study aimed to develop an artificial intelligence (AI) model to classify bone tumors in the proximal femur on plain radio...

Screening and functional prediction of differentially expressed genes in walnut endocarp during hardening period based on deep neural network under agricultural internet of things.

PloS one
The deep neural network is used to establish a neural network model to solve the problems of low accuracy and poor accuracy of traditional algorithms in screening differentially expressed genes and function prediction during the walnut endocarp harde...

Prediction of clinical trial enrollment rates.

PloS one
Clinical trials represent a critical milestone of translational and clinical sciences. However, poor recruitment to clinical trials has been a long standing problem affecting institutions all over the world. One way to reduce the cost incurred by ins...

Radiation Dose Reduction for 80-kVp Pediatric CT Using Deep Learning-Based Reconstruction: A Clinical and Phantom Study.

AJR. American journal of roentgenology
Deep learning-based reconstruction (DLR) may facilitate CT radiation dose reduction, but a paucity of literature has compared lower-dose DLR images with standard-dose iterative reconstruction (IR) images or explored application of DLR to low-tube-vo...

Weighted IForest and siamese GRU on small sample anomaly detection in healthcare.

Computer methods and programs in biomedicine
Background and objectiveAt present, many achievements have been made in anomaly detection of big data using deep neural network, However, in many practical application scenarios, there are still some problems, such as shortage of data, too large work...

Recent advances in predicting protein-protein interactions with the aid of artificial intelligence algorithms.

Current opinion in structural biology
Protein-protein interactions (PPIs) are essential in the regulation of biological functions and cell events, therefore understanding PPIs have become a key issue to understanding the molecular mechanism and investigating the design of drugs. Here we ...

Human health risk identification of petrochemical sites based on extreme gradient boosting.

Ecotoxicology and environmental safety
Petrochemical industry is a key industry of soil pollution, which presents great effects on human health and the ecological environment. It is of great significance to achieve rapid, economic and efficient health risk identification for petrochemical...

Knowledge Discovery on Cryptocurrency Exchange Rate Prediction Using Machine Learning Pipelines.

Sensors (Basel, Switzerland)
The popularity of cryptocurrency in recent years has gained a lot of attention among researchers and in academic working areas. The uncontrollable and untraceable nature of cryptocurrency offers a lot of attractions to the people in this domain. The ...

Missing-Sheds Granularity Estimation of Glass Insulators Using Deep Neural Networks Based on Optical Imaging.

Sensors (Basel, Switzerland)
Insulator defect detection is an important task in inspecting overhead transmission lines. However, the surrounding environment is complex, and the detection accuracy of traditional image processing algorithms is low. Therefore, insulator defect dete...