AIMC Topic: Decision Support Systems, Clinical

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A Machine Learning Shock Decision Algorithm for Use During Piston-Driven Chest Compressions.

IEEE transactions on bio-medical engineering
GOAL: Accurate shock decision methods during piston-driven cardiopulmonary resuscitation (CPR) would contribute to improve therapy and increase cardiac arrest survival rates. The best current methods are computationally demanding, and their accuracy ...

Big data and targeted machine learning in action to assist medical decision in the ICU.

Anaesthesia, critical care & pain medicine
Historically, personalised medicine has been synonymous with pharmacogenomics and oncology. We argue for a new framework for personalised medicine analytics that capitalises on more detailed patient-level data and leverages recent advances in causal ...

Stacked classifiers for individualized prediction of glycemic control following initiation of metformin therapy in type 2 diabetes.

Computers in biology and medicine
OBJECTIVE: Metformin is the preferred first-line medication for management of type 2 diabetes and prediabetes. However, over a third of patients experience primary or secondary therapeutic failure. We developed machine learning models to predict whic...

An improved support vector machine-based diabetic readmission prediction.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: In healthcare systems, the cost of unplanned readmission accounts for a large proportion of total hospital payment. Hospital-specific readmission rate becomes a critical issue around the world. Quantification and early ident...

Diagnosis of urinary tract infection based on artificial intelligence methods.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Urinary tract infection (UTI) is a common disease affecting the vast majority of people. UTI involves a simple infection caused by urinary tract inflammation as well as a complicated infection that may be caused by an inflam...

Creation of a Robust and Generalizable Machine Learning Classifier for Patient Ventilator Asynchrony.

Methods of information in medicine
BACKGROUND: As healthcare increasingly digitizes, streaming waveform data is being made available from an variety of sources, but there still remains a paucity of performant clinical decision support systems. For example, in the intensive care unit (...

Digital Diabetes Data and Artificial Intelligence: A Time for Humility Not Hubris.

Journal of diabetes science and technology
In the future artificial intelligence (AI) will have the potential to improve outcomes diabetes care. With the creation of new sensors for physiological monitoring sensors and the introduction of smart insulin pens, novel data relationships based on ...

eDoctor: machine learning and the future of medicine.

Journal of internal medicine
Machine learning (ML) is a burgeoning field of medicine with huge resources being applied to fuse computer science and statistics to medical problems. Proponents of ML extol its ability to deal with large, complex and disparate data, often found with...