AIMC Topic: Machine Learning

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Development of machine learning and natural language processing algorithms for preoperative prediction and automated identification of intraoperative vascular injury in anterior lumbar spine surgery.

The spine journal : official journal of the North American Spine Society
BACKGROUND: Intraoperative vascular injury (VI) may be an unavoidable complication of anterior lumbar spine surgery; however, vascular injury has implications for quality and safety reporting as this intraoperative complication may result in serious ...

An Integrated Approach of Machine Learning and Systems Thinking for Waiting Time Prediction in an Emergency Department.

International journal of medical informatics
OBJECTIVE: The objective of this study is to apply machine learning algorithms for real-time and personalized waiting time prediction in emergency departments. We also aim to introduce the concept of systems thinking to enhance the performance of the...

Enabling pregnant women and their physicians to make informed medication decisions using artificial intelligence.

Journal of pharmacokinetics and pharmacodynamics
The role of artificial intelligence (AI) in healthcare for pregnant women. To assess the role of AI in women's health, discover gaps, and discuss the future of AI in maternal health. A systematic review of English articles using EMBASE, PubMed, and S...

Roadmap for Developing Complex Virtual Reality Simulation Scenarios: Subpial Neurosurgical Tumor Resection Model.

World neurosurgery
BACKGROUND: Advancement and evolution of current virtual reality (VR) surgical simulation technologies are integral to improve the available armamentarium of surgical skill education. This is especially important in high-risk surgical specialties. Su...

Predicting Inpatient Medication Orders From Electronic Health Record Data.

Clinical pharmacology and therapeutics
In a general inpatient population, we predicted patient-specific medication orders based on structured information in the electronic health record (EHR). Data on over three million medication orders from an academic medical center were used to train ...

A computer vision approach for classifying isometric grip force exertion levels.

Ergonomics
Exposure to high and/or repetitive force exertions can lead to musculoskeletal injuries. However, measuring worker force exertion levels is challenging, and existing techniques can be intrusive, interfere with human-machine interface, and/or limited ...

Disease prediction via Bayesian hyperparameter optimization and ensemble learning.

BMC research notes
OBJECTIVE: Early disease screening and diagnosis are important for improving patient survival. Thus, identifying early predictive features of disease is necessary. This paper presents a comprehensive comparative analysis of different Machine Learning...