AI Medical Compendium Topic

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Data Mining

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Joint learning-based causal relation extraction from biomedical literature.

Journal of biomedical informatics
Causal relation extraction of biomedical entities is one of the most complex tasks in biomedical text mining, which involves two kinds of information: entity relations and entity functions. One feasible approach is to take relation extraction and fun...

A prefix and attention map discrimination fusion guided attention for biomedical named entity recognition.

BMC bioinformatics
BACKGROUND: The biomedical literature is growing rapidly, and it is increasingly important to extract meaningful information from the vast amount of literature. Biomedical named entity recognition (BioNER) is one of the key and fundamental tasks in b...

AI for life: Trends in artificial intelligence for biotechnology.

New biotechnology
Due to popular successes (e.g., ChatGPT) Artificial Intelligence (AI) is on everyone's lips today. When advances in biotechnology are combined with advances in AI unprecedented new potential solutions become available. This can help with many global ...

Design and Development of a Big Data Platform for Disease Burden Based on the Spark Engine.

Computational intelligence and neuroscience
OBJECTIVE: This study attempts to build a big data platform for disease burden that can realize the deep coupling of artificial intelligence and public health. This is a highly open and shared intelligent platform, including big data collection, anal...

Machine intelligence for radiation science: summary of the Radiation Research Society 67th annual meeting symposium.

International journal of radiation biology
The era of high-throughput techniques created big data in the medical field and research disciplines. Machine intelligence (MI) approaches can overcome critical limitations on how those large-scale data sets are processed, analyzed, and interpreted. ...

Defining Virtual Consumerism Through Content and Sentiment Analyses.

Cyberpsychology, behavior and social networking
This study set out to better understand virtual consumerism (VC) by applying natural language processing (NLP) methods for sentiment and content analyses. A total of 318 articles related to VC were identified on Web site and analyzed by text mining ...

Artificial Intelligence and Data Mining for the Pharmacovigilance of Drug-Drug Interactions.

Clinical therapeutics
Despite increasing mechanistic understanding, undetected and underrecognized drug-drug interactions (DDIs) persist. This elusiveness relates to an interwoven complexity of increasing polypharmacy, multiplex mechanistic pathways, and human biological ...

Artificial Intelligence in Medicine: Text Mining of Health Care Workers' Opinions.

Journal of medical Internet research
BACKGROUND: Artificial intelligence (AI) is being increasingly adopted in the health care industry for administrative tasks, patient care operations, and medical research.

Analysis of top box office film poster marketing scheme based on data mining and deep learning in the context of film marketing.

PloS one
With the development of science and technology and the continuous changes of social environment, the development prospect of traditional cinema is worrying. This work aims to improve the publicity effect of movie posters and optimize the marketing ef...

Prediction and Big Data Impact Analysis of Telecom Churn by Backpropagation Neural Network Algorithm from the Perspective of Business Model.

Big data
This study aims to transform the existing telecom operators from traditional Internet operators to digital-driven services, and improve the overall competitiveness of telecom enterprises. Data mining is applied to telecom user classification to proce...