AIMC Topic: Algorithms

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Water level prediction using soft computing techniques: A case study in the Malwathu Oya, Sri Lanka.

PloS one
Hydrologic models to simulate river flows are computationally costly. In addition to the precipitation and other meteorological time series, catchment characteristics, including soil data, land use, land cover, and roughness, are essential in most hy...

From Big Data's 5Vs to clinical practice's 5Ws: enhancing data-driven decision making in healthcare.

Journal of clinical monitoring and computing
The use of AI-based algorithms is rapidly growing in healthcare, but there is still an ongoing debate about how to manage and ensure accountability for their clinical use. While most of the studies focus on demonstrating a good algorithm performance ...

Portable deep-learning decoder for motor imaginary EEG signals based on a novel compact convolutional neural network incorporating spatial-attention mechanism.

Medical & biological engineering & computing
Due to high computational requirements, deep-learning decoders for motor imaginary (MI) electroencephalography (EEG) signals are usually implemented on bulky and heavy computing devices that are inconvenient for physical actions. To date, the applica...

Application of machine learning and deep learning methods for hydrated electron rate constant prediction.

Environmental research
Accurately determining the second-order rate constant with e (k) for organic compounds (OCs) is crucial in the e induced advanced reduction processes (ARPs). In this study, we collected 867 k values at different pHs from peer-reviewed publications an...

Tree-structured neural networks: Spatiotemporal dynamics and optimal control.

Neural networks : the official journal of the International Neural Network Society
How the network topology drives the response dynamic is a basic question that has not yet been fully answered in neural networks. Elucidating the internal relation between topological structures and dynamics is instrumental in our understanding of br...

A novel time series prediction method based on pooling compressed sensing echo state network and its application in stock market.

Neural networks : the official journal of the International Neural Network Society
In the prediction of time series, the echo state network (ESN) exhibits exclusive strengths and a unique training structure. Based on ESN model, a pooling activation algorithm consisting noise value and adjusted pooling algorithm is proposed to enric...

An enhanced Runge Kutta boosted machine learning framework for medical diagnosis.

Computers in biology and medicine
With the development and maturity of machine learning methods, medical diagnosis aided with machine learning methods has become a popular method to assist doctors in diagnosing and treating patients. However, machine learning methods are greatly affe...

Using artificial intelligence to reduce orthopedic surgical site infection surveillance workload: Algorithm design, validation, and implementation in 4 Spanish hospitals.

American journal of infection control
BACKGROUND: Surgical site infection (SSI) surveillance is a labor-intensive endeavor. We present the design and validation of an algorithm for SSI detection after hip replacement surgery, and a report of its successful implementation in 4 public hosp...

A Deep Learning Approach for Histology-Based Nucleus Segmentation and Tumor Microenvironment Characterization.

Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc
Microscopic examination of pathology slides is essential to disease diagnosis and biomedical research. However, traditional manual examination of tissue slides is laborious and subjective. Tumor whole-slide image (WSI) scanning is becoming part of ro...