AIMC Topic: Algorithms

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Optimized Attribute Selection Using Artificial Plant (AP) Algorithm with ESVM Classifier (AP-ESVM) and Improved Singular Value Decomposition (ISVD)-Based Dimensionality Reduction for Large Micro-array Biological Data.

Interdisciplinary sciences, computational life sciences
In the tremendous field of the bioinformatics look into, enormous volume of genetic information has been produced. Higher throughput gadgets are made accessible at lower cost made the age of Big data. In a time of developing information multifaceted ...

Automated classification of cancer from fine needle aspiration cytological image use neural networks: A meta-analysis.

Diagnostic cytopathology
BACKGROUND: The role of retrospective analysis has been evolved greatly in cancer research. We undertook this meta-analysis to evaluate the diagnostic value of Neural networks (NNs) in Fine needle aspiration cytological (FNAC) image of cancer.

Convolutional neural network for detection and classification of seizures in clinical data.

Medical & biological engineering & computing
Epileptic seizure detection and classification in clinical electroencephalogram data still is a challenge, and only low sensitivity with a high rate of false positives has been achieved with commercially available seizure detection tools, which usual...

Sensor-Array Optimization Based on Time-Series Data Analytics for Sanitation-Related Malodor Detection.

IEEE transactions on biomedical circuits and systems
There is an unmet need for a low-cost instrumented technology for detecting sanitation-related malodor as an alert for maintenance around shared toilets and emerging technologies for onsite waste treatment. In this article, our approach to an electro...

High-quality photoacoustic image reconstruction based on deep convolutional neural network: towards intra-operative photoacoustic imaging.

Biomedical physics & engineering express
The use of intra-operative imaging system as an intervention solution to provide more accurate localization of complicated structures has become a necessity during the neurosurgery. However, due to the limitations of conventional imaging systems, hig...

EEG-Brain Activity Monitoring and Predictive Analysis of Signals Using Artificial Neural Networks.

Sensors (Basel, Switzerland)
Predictive observation and real-time analysis of the values of biomedical signals and automatic detection of epileptic seizures before onset are beneficial for the development of warning systems for patients because the patient, once informed that an...

Artificial Neural Network Modeling of Novel Coronavirus (COVID-19) Incidence Rates across the Continental United States.

International journal of environmental research and public health
Prediction of the COVID-19 incidence rate is a matter of global importance, particularly in the United States. As of 4 June 2020, more than 1.8 million confirmed cases and over 108 thousand deaths have been reported in this country. Few studies have ...

Mid-price prediction based on machine learning methods with technical and quantitative indicators.

PloS one
Stock price prediction is a challenging task, in which machine learning methods have recently been successfully used. In this paper, we extract over 270 hand-crafted features (factors) inspired by technical indicators and quantitative analysis and te...

Binary CorNET: Accelerator for HR Estimation From Wrist-PPG.

IEEE transactions on biomedical circuits and systems
Research on heart rate (HR) estimation using wrist-worn photoplethysmography (PPG) sensors have progressed rapidly owing to the prominence of commercial sensing modules, used widely for lifestyle monitoring. Reported methodologies have been fairly su...

Electrical Impedance Tomography-Based Abdominal Subcutaneous Fat Estimation Method Using Deep Learning.

Computational and mathematical methods in medicine
This paper proposes a deep learning method based on electrical impedance tomography (EIT) to estimate the thickness of abdominal subcutaneous fat. EIT for evaluating the thickness of abdominal subcutaneous fat is an absolute imaging problem that aims...