AIMC Topic: Neural Networks, Computer

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Artificial neural networks in soil quality prediction: Significance for sustainable tea cultivation.

The Science of the total environment
In today's era artificial intelligence is quite popular, one of the most effective algorithms used is Artificial Neural Networks (ANN). In this study, the determination of soil quality using the Soil Management Assessment Framework (SMAF) model in ar...

Early Postoperative Prediction of Complications and Readmission After Colorectal Cancer Surgery Using an Artificial Neural Network.

Diseases of the colon and rectum
BACKGROUND: Early predictors of postoperative complications can risk-stratify patients undergoing colorectal cancer surgery. However, conventional regression models have limited power to identify complex nonlinear relationships among a large set of v...

Deep Learning-Based Real-Time Ureter Identification in Laparoscopic Colorectal Surgery.

Diseases of the colon and rectum
BACKGROUND: Iatrogenic ureteral injury is a serious complication of abdominopelvic surgery. Identifying the ureters intraoperatively is essential to avoid iatrogenic ureteral injury. We developed a model that may minimize this complication.

Predicting abrupt depletion of dissolved oxygen in Chaohu lake using CNN-BiLSTM with improved attention mechanism.

Water research
Depletion of dissolved oxygen (DO) is a significant incentive for biological catastrophic events in freshwater lakes. Although predicting the DO concentrations in lakes with high-frequency real-time data to prevent hypoxic events is effective, few re...

New strategy to optimize in-situ fenton oxidation for TPH contaminated soil remediation via artificial neural network approach.

Chemosphere
In-situ remediation of total petroleum hydrocarbon (TPH) contaminated soils via Fenton oxidation is a promising approach. However, determining the proper injection amount of HO and Fe source over the Fenton reaction in the complex geological conditio...

Neural Network-Based Filter Design for Compressive Raman Classification of Cells.

Journal of chemical information and modeling
Cell-based therapies are bound to revolutionize medicine, but significant technical hurdles must be overcome before wider adoption. In particular, nondestructive, label-free methods to characterize cells in real time are needed to optimize the produc...

Sharing massive biomedical data at magnitudes lower bandwidth using implicit neural function.

Proceedings of the National Academy of Sciences of the United States of America
Efficient storage and sharing of massive biomedical data would open up their wide accessibility to different institutions and disciplines. However, compressors tailored for natural photos/videos are rapidly limited for biomedical data, while emerging...

Investigation of ferroptosis-associated molecular subtypes and immunological characteristics in lupus nephritis based on artificial neural network learning.

Arthritis research & therapy
BACKGROUND: Lupus nephritis (LN) is a severe complication of systemic lupus erythematosus (SLE) with poor treatment outcomes. The role and underlying mechanisms of ferroptosis in LN remain largely unknown. We aimed to explore ferroptosis-related mole...

Tissue of origin detection for cancer tumor using low-depth cfDNA samples through combination of tumor-specific methylation atlas and genome-wide methylation density in graph convolutional neural networks.

Journal of translational medicine
BACKGROUND: Cell free DNA (cfDNA)-based assays hold great potential in detecting early cancer signals yet determining the tissue-of-origin (TOO) for cancer signals remains a challenging task. Here, we investigated the contribution of a methylation at...