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Artificial neural networks for simultaneously predicting the risk of multiple co-occurring symptoms among patients with cancer.

Cancer medicine
Patients with cancer often exhibit multiple co-occurring symptoms which can impact the type of treatment received, recovery, and long-term health. We aim to simultaneously predict the risk of three symptoms: severe pain, moderate-severe depression, a...

An embedded system for the automated generation of labeled plant images to enable machine learning applications in agriculture.

PloS one
A lack of sufficient training data, both in terms of variety and quantity, is often the bottleneck in the development of machine learning (ML) applications in any domain. For agricultural applications, ML-based models designed to perform tasks such a...

Web-based interactive mapping from data dictionaries to ontologies, with an application to cancer registry.

BMC medical informatics and decision making
BACKGROUND: The Kentucky Cancer Registry (KCR) is a central cancer registry for the state of Kentucky that receives data about incident cancer cases from all healthcare facilities in the state within 6 months of diagnosis. Similar to all other U.S. a...

Perceptions of Canadian radiation oncologists, radiation physicists, radiation therapists and radiation trainees about the impact of artificial intelligence in radiation oncology - national survey.

Journal of medical imaging and radiation sciences
BACKGROUND: Artificial Intelligence (AI) is making a continuous progression into the field of Radiation Oncology in Canada and globally. While this field continues to evolve, there is no clear understanding about how radiation oncologists, radiation ...

Deep Neural Network for Slip Detection on Ice Surface.

Sensors (Basel, Switzerland)
Slip-induced falls are among the most common causes of major occupational injuries and economic loss in Canada. Identifying the risk factors associated with slip events is key to developing preventive solutions to reduce falls. One factor is the slip...

A machine learning approach to predict ethnicity using personal name and census location in Canada.

PloS one
BACKGROUND: Canada is an ethnically-diverse country, yet its lack of ethnicity information in many large databases impedes effective population research and interventions. Automated ethnicity classification using machine learning has shown potential ...

Canadian Association of Radiologists White Paper on De-identification of Medical Imaging: Part 2, Practical Considerations.

Canadian Association of Radiologists journal = Journal l'Association canadienne des radiologistes
The application of big data, radiomics, machine learning, and artificial intelligence (AI) algorithms in radiology requires access to large data sets containing personal health information. Because machine learning projects often require collaboratio...

Canadian Association of Radiologists White Paper on De-Identification of Medical Imaging: Part 1, General Principles.

Canadian Association of Radiologists journal = Journal l'Association canadienne des radiologistes
The application of big data, radiomics, machine learning, and artificial intelligence (AI) algorithms in radiology requires access to large data sets containing personal health information. Because machine learning projects often require collaboratio...

Population health AI researchers' perceptions of the public portrayal of AI: A pilot study.

Public understanding of science (Bristol, England)
This article reports how 18 UK and Canadian population health artificial intelligence researchers in Higher Education Institutions perceive the use of artificial intelligence systems in their research, and how this compares with their perceptions abo...