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Medical Informatics

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Beginnings of Artificial Intelligence in Medicine (AIM): Computational Artifice Assisting Scientific Inquiry and Clinical Art - with Reflections on Present AIM Challenges.

Yearbook of medical informatics
BACKGROUND: The rise of biomedical expert heuristic knowledge-based approaches for computational modeling and problem solving, for scientific inquiry and medical decision-making, and for consultation in the 1970's led to a major change in the paradig...

Artificial intelligence in medical education.

Medical teacher
Artificial intelligence (AI) is a growing phenomenon, and will soon facilitate wide-scale changes in many professions, including medical education. In order for medical educators to be properly prepared for AI, they will need to have at least a funda...

Mining Implicit Treatment Concepts for Neural Precision Medicine.

IEEE transactions on nanobioscience
Precision medicine (PM) is regarded as an information retrieval (IR) task in which biomedical articles containing treatment information about specific diseases or genetic variants are retrieved in response to patient record for the purpose of providi...

Serendipity-A Machine-Learning Application for Mining Serendipitous Drug Usage From Social Media.

IEEE transactions on nanobioscience
Serendipitous drug usage refers to the unexpected relief of comorbid diseases or symptoms when taking medication for a different known indication. Historically, serendipity has contributed significantly to identifying many new drug indications. If pa...

Chinese Clinical Named Entity Recognition Using Residual Dilated Convolutional Neural Network With Conditional Random Field.

IEEE transactions on nanobioscience
Clinical named entity recognition (CNER) is a fundamental and crucial task for clinical and translation research. In recent years, deep learning methods have achieved significant success in CNER tasks. However, these methods depend greatly on recurre...

A deep learning-based decision support system for diagnosis of OSAS using PTT signals.

Medical hypotheses
Sleep disorders, which negatively affect an individual's daily quality of life, are a common problem for most of society. The most dangerous sleep disorder is obstructive sleep apnea syndrome (OSAS), which manifests itself during sleep and can cause ...

Harnessing the Power of Machine Learning in Dementia Informatics Research: Issues, Opportunities, and Challenges.

IEEE reviews in biomedical engineering
Dementia is a chronic and degenerative condition affecting millions globally. The care of patients with dementia presents an ever-continuing challenge to healthcare systems in the 21st century. Medical and health sciences have generated unprecedented...

Reinforcement learning-based control of tumor growth under anti-angiogenic therapy.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVES: In recent decades, cancer has become one of the most fatal and destructive diseases which is threatening humans life. Accordingly, different types of cancer treatment are studied with the main aim to have the best treatment...

Machine Learning in Relation to Emergency Medicine Clinical and Operational Scenarios: An Overview.

The western journal of emergency medicine
Health informatics is a vital technology that holds great promise in the healthcare setting. We describe two prominent health informatics tools relevant to emergency care, as well as the historical background and the current state of informatics. We ...