AI Medical Compendium Topic

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Data Mining

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Discrepancies in Stroke Distribution and Dataset Origin in Machine Learning for Stroke.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
BACKGROUND: Machine learning algorithms depend on accurate and representative datasets for training in order to become valuable clinical tools that are widely generalizable to a varied population. We aim to conduct a review of machine learning uses i...

Construction data mining methods in the prediction of death in hemodialysis patients using support vector machine, neural network, logistic regression and decision tree.

Journal of preventive medicine and hygiene
OBJECTIVES: Chronic kidney disease (CKD) is one of the main causes of morbidity and mortality worldwide. Detecting survival modifiable factors could help in prioritizing the clinical care and offers a treatment decision-making for hemodialysis patien...

A primer on applying AI synergistically with domain expertise to oncology.

Biochimica et biophysica acta. Reviews on cancer
BACKGROUND: The concurrent growth of large-scale oncology data alongside the computational methods with which to analyze and model it has created a promising environment for revolutionizing cancer diagnosis, treatment, prevention, and drug discovery....

Extracting knowledge networks from plant scientific literature: potato tuber flesh color as an exemplary trait.

BMC plant biology
BACKGROUND: Scientific literature carries a wealth of information crucial for research, but only a fraction of it is present as structured information in databases and therefore can be analyzed using traditional data analysis tools. Natural language ...

IrGO: Iranian traditional medicine General Ontology and knowledge base.

Journal of biomedical semantics
BACKGROUND: Iranian traditional medicine, also known as Persian Medicine, is a holistic school of medicine with a long prolific history. It describes numerous concepts and the relationships between them. However, no unified language system has been p...

Automatic Search-and-Replace From Examples With Coevolutionary Genetic Programming.

IEEE transactions on cybernetics
We describe the design and implementation of a system for executing search-and-replace text processing tasks automatically, based only on examples of the desired behavior. The examples consist of pairs describing the original string and the desired m...

Artificial intelligence to deep learning: machine intelligence approach for drug discovery.

Molecular diversity
Drug designing and development is an important area of research for pharmaceutical companies and chemical scientists. However, low efficacy, off-target delivery, time consumption, and high cost impose a hurdle and challenges that impact drug design a...

Improved characterisation of clinical text through ontology-based vocabulary expansion.

Journal of biomedical semantics
BACKGROUND: Biomedical ontologies contain a wealth of metadata that constitutes a fundamental infrastructural resource for text mining. For several reasons, redundancies exist in the ontology ecosystem, which lead to the same entities being described...

Core services that power AI-driven transformation in cancer research and care.

Biochimica et biophysica acta. Reviews on cancer
This review captures some key lessons learned in the course of helping some of America's leading healthcare AI innovators achieve scale and sustained impact in complex research and care delivery ecosystems. AI innovators may find it useful to access ...

Local-Global Memory Neural Network for Medication Prediction.

IEEE transactions on neural networks and learning systems
Electronic medical records (EMRs) play an important role in medical data mining and sequential data learning. In this article, we propose to use a sequential neural network with dynamic content-based memories to predict future medications, given EMRs...