AIMC Topic: Machine Learning

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Applications of Artificial Intelligence in Pediatric Oncology: A Systematic Review.

JCO clinical cancer informatics
PURPOSE: There is a need for an improved understanding of clinical and biologic risk factors in pediatric cancer to improve patient outcomes. Machine learning (ML) represents the application of computational inference from advanced statistical method...

Realizing the Power of Text Mining and Natural Language Processing for Analyzing Patient Safety Event Narratives: The Challenges and Path Forward.

Journal of patient safety
Patient safety event (PSE) reports are a useful lens to understand hazards and patient safety risks in healthcare systems. However, patient safety officers and analysts in healthcare systems and safety organizations are challenged to make sense of th...

Interpretation and reporting of predictive or diagnostic machine-learning research in Trauma & Orthopaedics.

The bone & joint journal
There is increasing popularity in the use of artificial intelligence and machine-learning techniques to provide diagnostic and prognostic models for various aspects of Trauma & Orthopaedic surgery. However, correct interpretation of these models is d...

Augmenting Osteoporosis Imaging with Machine Learning.

Current osteoporosis reports
PURPOSE OF REVIEW: In this paper, we discuss how recent advancements in image processing and machine learning (ML) are shaping a new and exciting era for the osteoporosis imaging field. With this paper, we want to give the reader a basic exposure to ...

Using artificial intelligence to automate meat cut identification from the semimembranosus muscle on beef boning lines.

Journal of animal science
The identification of different meat cuts for labeling and quality control on production lines is still largely a manual process. As a result, it is a labor-intensive exercise with the potential for not only error but also bacterial cross-contaminati...

Learning From an Association Analysis Using Propensity Scores.

Pediatric critical care medicine : a journal of the Society of Critical Care Medicine and the World Federation of Pediatric Intensive and Critical Care Societies

Machine learning for the identification of decision boundaries during the transition from radial to vertical growth phase superficial spreading melanomas.

Melanoma research
The objective of this study was to compute threshold values for the diameter of superficial spreading melanomas (SSMs) at which the radial growth phase (RGP) evolves into an invasive vertical growth phase (VGP). We examined reports from 1995 to 2019 ...