AIMC Topic: Machine Learning

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rECHOmmend: An ECG-Based Machine Learning Approach for Identifying Patients at Increased Risk of Undiagnosed Structural Heart Disease Detectable by Echocardiography.

Circulation
BACKGROUND: Timely diagnosis of structural heart disease improves patient outcomes, yet many remain underdiagnosed. While population screening with echocardiography is impractical, ECG-based prediction models can help target high-risk patients. We de...

Dynamic Learning Framework for Smooth-Aided Machine-Learning-Based Backbone Traffic Forecasts.

Sensors (Basel, Switzerland)
Recently, there has been an increasing need for new applications and services such as big data, blockchains, vehicle-to-everything (V2X), the Internet of things, 5G, and beyond. Therefore, to maintain quality of service (QoS), accurate network resour...

A Review of Fundamental Optimization Approaches and the Role of AI Enabling Technologies in Physical Layer Security.

Sensors (Basel, Switzerland)
With the proliferation of 5G mobile networks within next-generation wireless communication, the design and optimization of 5G networks are progressing in the direction of improving the physical layer security (PLS) paradigm. This phenomenon is due to...

Modeling of energy consumption factors for an industrial cement vertical roller mill by SHAP-XGBoost: a "conscious lab" approach.

Scientific reports
Cement production is one of the most energy-intensive manufacturing industries, and the milling circuit of cement plants consumes around 4% of a year's global electrical energy production. It is well understood that modeling and digitalizing industri...

Assessment and Evaluation of Different Machine Learning Algorithms for Predicting Student Performance.

Computational intelligence and neuroscience
Student performance is crucial to the success of tertiary institutions. Especially, academic achievement is one of the metrics used in rating top-quality universities. Despite the large volume of educational data, accurately predicting student perfor...

Artificial Intelligence: A Universal Virtual Tool to Augment Tutoring in Higher Education.

Computational intelligence and neuroscience
Artificial intelligence is an emerging technology that revolutionizes human lives. Despite the fact that this technology is used in higher education, many professors are unaware of it. In this current scenario, there is a huge need to arise, implemen...

Research on Earnings Management of Growth Enterprise Market in China Stock Market: Comparative Analysis Based on the BPNN, GBDT, and MLR Models.

Computational intelligence and neuroscience
This study, based on 2011-2020 China's listed companies on GEM as research samples, introduces the BPNN (BP neural network) and GBDT (Gradient Boosting Decision Tree) model into the research of the relationship between internal governance and earning...

ZeVigilante: Detecting Zero-Day Malware Using Machine Learning and Sandboxing Analysis Techniques.

Computational intelligence and neuroscience
For the enormous growth and the hysterical impact of undocumented malicious software, otherwise known as Zero-Day malware, specialized practices were joined to implement systems capable of detecting these kinds of software to avert possible disastrou...

Beyond technology: Can artificial intelligence support clinical decisions in the prediction of sepsis?

Revista brasileira de enfermagem
OBJECTIVE: To analyze the critical alarms predictors of clinical deterioration/sepsis for clinical decision making in patients admitted to a reference hospital complex.

Identifying Protein Features and Pathways Responsible for Toxicity Using Machine Learning and Tox21: Implications for Predictive Toxicology.

Molecules (Basel, Switzerland)
Humans are exposed to numerous compounds daily, some of which have adverse effects on health. Computational approaches for modeling toxicological data in conjunction with machine learning algorithms have gained popularity over the last few years. Mac...