AI Medical Compendium Topic

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Data Science

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Bottom-up and top-down paradigms of artificial intelligence research approaches to healthcare data science using growing real-world big data.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVES: As the real-world electronic health record (EHR) data continue to grow exponentially, novel methodologies involving artificial intelligence (AI) are becoming increasingly applied to enable efficient data-driven learning and, ultimately, t...

Analysis of COVID-19 Vaccinations and Symptom Mapping Diagnostic Technique for Viral Diseases: Using Data Analytics, Machine Learning, and Artificial Intelligence.

Inquiry : a journal of medical care organization, provision and financing
To analyze, understand, and measure the COVID-19 vaccination outlook in a developing country as Nigeria; and the non-clinical analysis, diagnosis, treatment and management of COVID-19, and other Viral Diseases, using Data/Machine Learning (ML)/Artifi...

How data science and AI-based technologies impact genomics.

Singapore medical journal
Advancements in high-throughput sequencing have yielded vast amounts of genomic data, which are studied using genome-wide association study (GWAS)/phenome-wide association study (PheWAS) methods to identify associations between the genotype and pheno...

[Drug discovery research using AI and data science: analyzing literature information to understand pathological mechanisms].

Nihon yakurigaku zasshi. Folia pharmacologica Japonica
Recent rapid progress in big data and breakthrough AI technologies have brought about significant changes in the medical field as well. Although biomedical literature databases contain so many articles that it is impossible to read them all, AI techn...

ASAS-NANP symposium: mathematical modeling in animal nutrition: the progression of data analytics and artificial intelligence in support of sustainable development in animal science.

Journal of animal science
A renewed interest in data analytics and decision support systems in developing automated computer systems is facilitating the emergence of hybrid intelligent systems by combining artificial intelligence (AI) algorithms with classical modeling paradi...

An Ontology for Cardiothoracic Surgical Education and Clinical Data Analytics.

Studies in health technology and informatics
The development of an ontology facilitates the organization of the variety of concepts used to describe different terms in different resources. The proposed ontology will facilitate the study of cardiothoracic surgical education and data analytics in...

From space to biomedicine: Enabling biomarker data science in the cloud.

Cancer biomarkers : section A of Disease markers
NASA's Jet Propulsion Laboratory (JPL) is advancing research capabilities for data science with two of the National Cancer Institute's major research programs, the Early Detection Research Network (EDRN) and the Molecular and Cellular Characterizatio...

Glycowork: A Python package for glycan data science and machine learning.

Glycobiology
While glycans are crucial for biological processes, existing analysis modalities make it difficult for researchers with limited computational background to include these diverse carbohydrates into workflows. Here, we present glycowork, an open-source...

Surgical data science and artificial intelligence for surgical education.

Journal of surgical oncology
Surgical data science (SDS) aims to improve the quality of interventional healthcare and its value through the capture, organization, analysis, and modeling of procedural data. As data capture has increased and artificial intelligence (AI) has advanc...