AIMC Topic: Machine Learning

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Evolution of Machine Learning Algorithms in the Prediction and Design of Anticancer Peptides.

Current protein & peptide science
Peptides act as promising anticancer agents due to their ease of synthesis and modifications, enhanced tumor penetration, and less systemic toxicity. However, only limited success has been achieved so far, as experimental design and synthesis of anti...

An Overview on Predicting Protein Subchloroplast Localization by using Machine Learning Methods.

Current protein & peptide science
The chloroplast is a type of subcellular organelle of green plants and eukaryotic algae, which plays an important role in the photosynthesis process. Since the function of a protein correlates with its location, knowing its subchloroplast localizatio...

Does machine learning improve prediction of VA primary care reliance?

The American journal of managed care
OBJECTIVES: The Veterans Affairs (VA) Health Care System is among the largest integrated health systems in the United States. Many VA enrollees are dual users of Medicare, and little research has examined methods to most accurately predict which vete...

[Machine learning in radiology : Terminology from individual timepoint to trajectory].

Der Radiologe
METHODICAL ISSUE: Machine learning (ML) algorithms have an increasingly relevant role in radiology tackling tasks such as the automatic detection and segmentation of diagnosis-relevant markers, the quantification of progression and response, and thei...

A Machine Learning-Based Model to Predict Acute Traumatic Coagulopathy in Trauma Patients Upon Emergency Hospitalization.

Clinical and applied thrombosis/hemostasis : official journal of the International Academy of Clinical and Applied Thrombosis/Hemostasis
Acute traumatic coagulopathy (ATC) is an extremely common but silent murderer; this condition presents early after trauma and impacts approximately 30% of severely injured patients who are admitted to emergency departments (EDs). Given that conventio...

Reducing False Alarm Rates in Neonatal Intensive Care: A New Machine Learning Approach.

Advances in experimental medicine and biology
UNLABELLED: In neonatal intensive care units (NICUs), 87.5% of alarms by the monitoring system are false alarms, often caused by the movements of the neonates. Such false alarms are not only stressful for the neonates as well as for their parents and...