AI Medical Compendium Topic

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Decision Support Techniques

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Development of an intelligent surgical training system for Thoracentesis.

Artificial intelligence in medicine
Surgical training improves patient care, helps to reduce surgical risks, increases surgeon's confidence, and thus enhances overall patient safety. Current surgical training systems are more focused on developing technical skills, e.g. dexterity, of t...

Sequence-Based Prediction of Cysteine Reactivity Using Machine Learning.

Biochemistry
As one of the most intrinsically reactive amino acids, cysteine carries a variety of important biochemical functions, including catalysis and redox regulation. Discovery and characterization of cysteines with heightened reactivity will help annotate ...

Learning ensemble classifiers for diabetic retinopathy assessment.

Artificial intelligence in medicine
Diabetic retinopathy is one of the most common comorbidities of diabetes. Unfortunately, the recommended annual screening of the eye fundus of diabetic patients is too resource-consuming. Therefore, it is necessary to develop tools that may help doct...

Temporal case-based reasoning for type 1 diabetes mellitus bolus insulin decision support.

Artificial intelligence in medicine
Individuals with type 1 diabetes have to monitor their blood glucose levels, determine the quantity of insulin required to achieve optimal glycaemic control and administer it themselves subcutaneously, multiple times per day. To help with this proces...

Machine Learning and Neurosurgical Outcome Prediction: A Systematic Review.

World neurosurgery
OBJECTIVE: Accurate measurement of surgical outcomes is highly desirable to optimize surgical decision-making. An important element of surgical decision making is identification of the patient cohort that will benefit from surgery before the interven...

Estimation and evaluation of linear individualized treatment rules to guarantee performance.

Biometrics
In clinical practice, an informative and practically useful treatment rule should be simple and transparent. However, because simple rules are likely to be far from optimal, effective methods to construct such rules must guarantee performance, in ter...

Single Nucleotide Polymorphism relevance learning with Random Forests for Type 2 diabetes risk prediction.

Artificial intelligence in medicine
OBJECTIVE: The use of artificial intelligence techniques to find out which Single Nucleotide Polymorphisms (SNPs) promote the development of a disease is one of the features of medical research, as such techniques may potentially aid early diagnosis ...