AIMC Topic: Support Vector Machine

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Corn Seed Freezing Damage Identification of Different Sides Based on Hyperspectral Imaging and SPA-2DCOS Fusion Algorithm.

Molecules (Basel, Switzerland)
In order to improve the utilization efficiency of corn seeds and meet the demand of single-seed seeding technology in agriculture, this study was conducted to explore the effect of freezing damage detection on the endosperm and embryo sides of single...

Towards Multiple Sclerosis Personalised Interventions Based on Real-World Predictive Analytics.

Studies in health technology and informatics
This study investigates the use of machine learning (ML) techniques to predict intervention response in patients with Multiple Sclerosis (PwMS) using real-world data from wearable devices. Data from 27 PwMS, monitored over two months were analyzed wi...

Hierarchical clustering analysis & machine learning models for diagnosing skeletal classes I and II in German patients.

BMC oral health
BACKGROUND: Classification is one of the most common tasks in artificial intelligence (AI) driven fields in dentistry and orthodontics. The AI abilities can significantly improve the orthodontist's critical mission to diagnose and treat patients prec...

Artificial intelligence for severity triage based on conversations in an emergency department in Korea.

Scientific reports
In the fast-paced emergency departments, where crises unfold unpredictably, the systematic prioritization of critical patients based on a severity classification is vital for swift and effective treatment. This study aimed to enhance the quality of e...

A machine-learning-integrated portable electrochemiluminescence sensing platform for the visualization and high-throughput immunoassays.

Talanta
Electrochemiluminescence (ECL)-based point-of-care testing (POCT) has the potential to facilitate the rapid identification of diseases, offering advantages such as high sensitivity, strong selectivity, and minimal background interference. However, as...

Prediction models based on machine learning algorithms for COVID-19 severity risk.

BMC public health
BACKGROUND: The World Health Organization has highlighted the risk of Disease X, urging pandemic preparedness. Coronavirus disease 2019 (COVID-19) could be the first Disease X; therefore, understanding the epidemiological experiences of COVID-19 is c...

Revolutionizing sleep disorder diagnosis: A Multi-Task learning approach optimized with genetic and Q-Learning techniques.

Scientific reports
Adequate sleep is crucial for maintaining a healthy lifestyle, and its deficiency can lead to various sleep-related disorders. Identifying these disorders early is essential for effective treatment, which traditionally relies on polysomnogram (PSG) t...

Optimized SVR with nature-inspired algorithms for environmental modelling of mycotoxins in food virtual-water samples.

Scientific reports
The accurate determination of mycotoxins in food samples is crucial to guarantee food safety and minimize their toxic effects on human and animal health. This study proposed the use of a support vector regression (SVR) predictive model improved by tw...

Early detection of mental health disorders using machine learning models using behavioral and voice data analysis.

Scientific reports
People of all demographics are impacted by mental illness, which has become a widespread and international health problem. Effective treatment and support for mental illnesses depend on early discovery and precise diagnosis. Notably, delayed diagnosi...

Intelligent Olfactory System Utilizing Ceria Nanoparticle-Integrated Laser-Induced Graphene.

ACS nano
The digitization of human senses has driven innovation across various technologies and transformed our daily lives, yet the digitization of olfaction remains a challenging frontier. Artificial olfactory systems, or electronic noses (e-noses), offer g...