AIMC Topic: Machine Learning

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evERdock BAI: Machine-learning-guided selection of protein-protein complex structure.

The Journal of chemical physics
Computational techniques for accurate and efficient prediction of protein-protein complex structures are widely used for elucidating protein-protein interactions, which play important roles in biological systems. Recently, it has been reported that s...

Artificial Intelligence Distinguishes Surgical Training Levels in a Virtual Reality Spinal Task.

The Journal of bone and joint surgery. American volume
BACKGROUND: With the emergence of competency-based training, the current evaluation scheme of surgical skills is evolving to include newer methods of assessment and training. Artificial intelligence through machine learning algorithms can utilize ext...

Machine learning approaches to study glioblastoma: A review of the last decade of applications.

Cancer reports (Hoboken, N.J.)
BACKGROUND: Glioblastoma (GB, formally glioblastoma multiforme) is a malignant type of brain cancer that currently has no cure and is characterized by being highly heterogeneous with high rates of re-incidence and therapy resistance. Thus, it is urge...

Network physiology in insomnia patients: Assessment of relevant changes in network topology with interpretable machine learning models.

Chaos (Woodbury, N.Y.)
Network physiology describes the human body as a complex network of interacting organ systems. It has been applied successfully to determine topological changes in different sleep stages. However, the number of network links can quickly grow above th...

Medical Big Data Is Not Yet Available: Why We Need Realism Rather than Exaggeration.

Endocrinology and metabolism (Seoul, Korea)
Most people are now familiar with the concepts of big data, deep learning, machine learning, and artificial intelligence (AI) and have a vague expectation that AI using medical big data can be used to improve the quality of medical care. However, the...

A future of automated image contouring with machine learning in radiation therapy.

Journal of medical radiation sciences
Automated image contouring is showing improvements in efficiency for a number of clinical tasks in radiotherapy. While atlas segmentation has proven moderately beneficial, the next generation of algorithms based on convolutional neural networks is al...

Diagnostic accuracy of machine-learning-assisted detection for anterior cruciate ligament injury based on magnetic resonance imaging: Protocol for a systematic review and meta-analysis.

Medicine
BACKGROUND: Although many machine learning algorithms have been developed to detect anterior cruciate ligament (ACL) injury based on magnetic resonance imaging (MRI), the performance of different algorithms required further investigation. The objecti...

Super-resolution recurrent convolutional neural networks for learning with multi-resolution whole slide images.

Journal of biomedical optics
We study a problem scenario of super-resolution (SR) algorithms in the context of whole slide imaging (WSI), a popular imaging modality in digital pathology. Instead of just one pair of high- and low-resolution images, which is typically the setup in...

A Machine Learning-Based Triage Tool for Children With Acute Infection in a Low Resource Setting.

Pediatric critical care medicine : a journal of the Society of Critical Care Medicine and the World Federation of Pediatric Intensive and Critical Care Societies
OBJECTIVES: To deploy machine learning tools (random forests) to develop a model that reliably predicts hospital mortality in children with acute infections residing in low- and middle-income countries, using age and other variables collected at hosp...