AIMC Topic: Support Vector Machine

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Environmental Affection-Driven English Tense Analysis: A Healthcare Exercise-Based Corpus Case Study over Public English Environment.

Journal of environmental and public health
Most international academic papers are written in English, and the use of tenses in English academic papers often follows some conventional rules. Automatically extracting and analyzing English tenses in scientific papers have begun to attract resear...

Dynamic Data Infrastructure Security for Interoperable e-Healthcare Systems: A Semantic Feature-Driven NoSQL Intrusion Attack Detection Model.

BioMed research international
The exponential rise in advanced software computing and low-cost hardware has broadened the horizon for the Internet of Medical Things (IoMT), interoperable e-Healthcare systems serving varied purposes including electronic healthcare records (EHRs) a...

Sunken oil detection and classification using MBES backscatter data.

Marine pollution bulletin
Sunken oil incidents have occurred multiple times in the Bohai Sea over the past ten years. Currently, quick and effective sunken oil detection and classification remains a difficult problem. In this study, sonar detection experiments are conducted t...

Breast Tumor Detection Using Robust and Efficient Machine Learning and Convolutional Neural Network Approaches.

Computational intelligence and neuroscience
Breast cancer develops when cells in the breast expand and divide uncontrollably, resulting in a lump of tissue known as a tumor. This lump of tissue is called a tumor. After skin cancer, breast cancer is the second most common cancer among women. It...

Empirical Method for Thyroid Disease Classification Using a Machine Learning Approach.

BioMed research international
There are many thyroid diseases affecting people all over the world. Many diseases affect the thyroid gland, like hypothyroidism, hyperthyroidism, and thyroid cancer. Thyroid inefficiency can cause severe symptoms in patients. Effective classificatio...

A novel method for feature selection based on molecular interactive effect network.

Journal of pharmaceutical and biomedical analysis
Analyzing the biological data by considering the molecule interactions may induce a more accurate identification of disease-related biomarkers. In this study, a novel feature selection method based on molecule (feature) interactive effect network is ...

A Combined Sensing System for Intrusion Detection Using Anti-Jamming Random Code Signals.

Sensors (Basel, Switzerland)
In order to prevent illegal intrusion, theft, and destruction, important places require stable and reliable human intrusion detection technology to maintain security. In this paper, a combined sensing system using anti-jamming random code signals is ...

An efficient model of residual based convolutional neural network with Bayesian optimization for the classification of malarial cell images.

Computers in biology and medicine
BACKGROUND: Malaria is a disease caused by the Plasmodium parasite, which results in millions of deaths in the human population worldwide each year. It is therefore considered a major global health issue with a massive disease burden. Accurate and ra...

Neuropsychological test using machine learning for cognitive impairment screening.

Applied neuropsychology. Adult
OBJECTIVES: Neuropsychological tests (NPTs) are widely used tools to evaluate cognitive functioning. The interpretation of these tests can be time-consuming and requires a specialized clinician. For this reason, we trained machine learning models tha...

Feature selection for global tropospheric ozone prediction based on the BO-XGBoost-RFE algorithm.

Scientific reports
Ozone is one of the most important air pollutants, with significant impacts on human health, regional air quality and ecosystems. In this study, we use geographic information and environmental information of the monitoring site of 5577 regions in the...