AIMC Topic: Algorithms

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Development and External Validation of a Deep Learning Algorithm to Identify and Localize Subarachnoid Hemorrhage on CT Scans.

Neurology
BACKGROUND AND OBJECTIVES: In medical imaging, a limited number of trained deep learning algorithms have been externally validated and released publicly. We hypothesized that a deep learning algorithm can be trained to identify and localize subarachn...

Big data and machine learning driven bioprocessing - Recent trends and critical analysis.

Bioresource technology
Given the potential of machine learning algorithms in revolutionizing the bioengineering field, this paper examined and summarized the literature related to artificial intelligence (AI) in the bioprocessing field. Natural language processing (NLP) wa...

Automated warfarin dose prediction for Asian, American, and Caucasian populations using a deep neural network.

Computers in biology and medicine
Existing warfarin dose prediction algorithms based on pharmacogenetics and clinical parameters have not been used clinically due to the absence of external validation, lack of assessment for clinical utility, and high risk of bias. Moreover, given th...

Application of artificial intelligence to stereotactic radiosurgery for intracranial lesions: detection, segmentation, and outcome prediction.

Journal of neuro-oncology
BACKGROUND: Rapid evolution of artificial intelligence (AI) prompted its wide application in healthcare systems. Stereotactic radiosurgery served as a good candidate for AI model development and achieved encouraging result in recent years. This artic...

Construction Site Safety Management: A Computer Vision and Deep Learning Approach.

Sensors (Basel, Switzerland)
In this study, we used image recognition technology to explore different ways to improve the safety of construction workers. Three object recognition scenarios were designed for safety at a construction site, and a corresponding object recognition mo...

Neural Network in the Analysis of the MR Signal as an Image Segmentation Tool for the Determination of T and T Relaxation Times with Application to Cancer Cell Culture.

International journal of molecular sciences
Artificial intelligence has been entering medical research. Today, manufacturers of diagnostic instruments are including algorithms based on neural networks. Neural networks are quickly entering all branches of medical research and beyond. Analyzing ...

Ethics and governance of trustworthy medical artificial intelligence.

BMC medical informatics and decision making
BACKGROUND: The growing application of artificial intelligence (AI) in healthcare has brought technological breakthroughs to traditional diagnosis and treatment, but it is accompanied by many risks and challenges. These adverse effects are also seen ...

Implementing machine learning methods with complex survey data: Lessons learned on the impacts of accounting sampling weights in gradient boosting.

PloS one
Despite the prominent use of complex survey data and the growing popularity of machine learning methods in epidemiologic research, few machine learning software implementations offer options for handling complex samples. A major challenge impeding th...

Applications of Artificial Intelligence and Deep Learning in Glaucoma.

Asia-Pacific journal of ophthalmology (Philadelphia, Pa.)
Diagnosis and detection of progression of glaucoma remains challenging. Artificial intelligence-based tools have the potential to improve and standardize the assessment of glaucoma but development of these algorithms is difficult given the multimodal...