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Bayes Theorem

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Synthesizing theories of human language with Bayesian program induction.

Nature communications
Automated, data-driven construction and evaluation of scientific models and theories is a long-standing challenge in artificial intelligence. We present a framework for algorithmically synthesizing models of a basic part of human language: morpho-pho...

Sparse Bayesian Model and Artificial Intelligence in Enterprise Goodwill Evaluation and Dynamic Management.

Computational intelligence and neuroscience
With the rapid development of mobile Internet information technology, automated search text has occupied a leading position in many industries. This article not only makes a detailed case study on the basic working principles of text feature extracti...

Facial Expression Recognition Based on LDA Feature Space Optimization.

Computational intelligence and neuroscience
With the development of artificial intelligence, facial expression recognition has become an important part of the current research due to its wide application potential. However, the qualities of the face features will directly affect the accuracy o...

Machine Learning and Lexicon Approach to Texts Processing in the Detection of Degrees of Toxicity in Online Discussions.

Sensors (Basel, Switzerland)
This article focuses on the problem of detecting toxicity in online discussions. Toxicity is currently a serious problem when people are largely influenced by opinions on social networks. We offer a solution based on classification models using machi...

EpICC: A Bayesian neural network model with uncertainty correction for a more accurate classification of cancer.

Scientific reports
Accurate classification of cancers into their types and subtypes holds the key for choosing the right treatment strategy and can greatly impact patient well-being. However, existence of large-scale variations in the molecular processes driving even a...

Managing and Retrieving Bilingual Documents Using Artificial Intelligence-Based Ontological Framework.

Computational intelligence and neuroscience
In recent times, artificial intelligence (AI) methods have been applied in document and content management to make decisions and improve the organization's functionalities. However, the lack of semantics and restricted metadata hinders the current do...

An Assessment of Lexical, Network, and Content-Based Features for Detecting Malicious URLs Using Machine Learning and Deep Learning Models.

Computational intelligence and neuroscience
The World Wide Web services are essential in our daily lives and are available to communities through Uniform Resource Locator (URL). Attackers utilize such means of communication and create malicious URLs to conduct fraudulent activities and deceive...

Machine learning to predict adverse outcomes after cardiac surgery: A systematic review and meta-analysis.

Journal of cardiac surgery
BACKGROUND: Machine learning (ML) models are promising tools for predicting adverse postoperative outcomes in cardiac surgery, yet have not translated to routine clinical use. We conducted a systematic review and meta-analysis to assess the predictiv...

Classification of Musculoskeletal Radiograph Requisition Appropriateness Using Machine Learning.

Canadian Association of Radiologists journal = Journal l'Association canadienne des radiologistes
Poor quality imaging requisitions lower report quality and impede good patient care. Manual control of such requisitions is time consuming and can be a source of friction with referring physicians. The purpose of this study was to determine if poor ...

Machine-learning models for predicting surgical site infections using patient pre-operative risk and surgical procedure factors.

American journal of infection control
BACKGROUND: Surgical site infections (SSIs) are a significant health care problem as they can cause increased medical costs and increased morbidity and mortality. Assessing a patient's preoperative risk factors can improve risk stratification and hel...