AIMC Topic: Automation

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Reacting and responding to rare, uncertain and unprecedented events.

Ergonomics
This work examines how we may be able to anticipate, respond to, and train for the occurrence of rare, uncertain, and unexpected events in human-machine systems operations. In particular, it uses a foundational matrix which describes the combinations...

Identification of Preanesthetic History Elements by a Natural Language Processing Engine.

Anesthesia and analgesia
BACKGROUND: Methods that can automate, support, and streamline the preanesthesia evaluation process may improve resource utilization and efficiency. Natural language processing (NLP) involves the extraction of relevant information from unstructured t...

Deep Learning Automation of Kidney, Liver, and Spleen Segmentation for Organ Volume Measurements in Autosomal Dominant Polycystic Kidney Disease.

Tomography (Ann Arbor, Mich.)
Organ volume measurements are a key metric for managing ADPKD (the most common inherited renal disease). However, measuring organ volumes is tedious and involves manually contouring organ outlines on multiple cross-sectional MRI or CT images. The aut...

Deep Learning and Transfer Learning for Malaria Detection.

Computational intelligence and neuroscience
Infectious disease malaria is a devastating infectious disease that claims the lives of more than 500,000 people worldwide every year. Most of these deaths occur as a result of a delayed or incorrect diagnosis. At the moment, the manual microscope is...

Applications of Artificial Intelligence and Machine Learning Algorithms to Crystallization.

Chemical reviews
Artificial intelligence and specifically machine learning applications are nowadays used in a variety of scientific applications and cutting-edge technologies, where they have a transformative impact. Such an assembly of statistical and linear algebr...

Automation of dry eye disease quantitative assessment: A review.

Clinical & experimental ophthalmology
Dry eye disease (DED) is a common eye condition worldwide and a primary reason for visits to the ophthalmologist. DED diagnosis is performed through a combination of tests, some of which are unfortunately invasive, non-reproducible and lack accuracy....

Artificial Neural Network Model for Indoor Decoration Intelligence Calculation and Automation Design.

Computational intelligence and neuroscience
With the continuous development of science and technology, the indoor decoration industry has gradually changed toward mechanization, specialization, and intelligent direction. Based on the predecessor research, this study proposes an artificial neur...

Automation of Cephalometrics Using Machine Learning Methods.

Computational intelligence and neuroscience
Cephalometry is a medical test that can detect teeth, skeleton, or appearance problems. In this scenario, the patient's lateral radiograph of the face was utilised to construct a tracing from the tracing of lines on the lateral radiograph of the face...

A novel tool that allows interactive screening of PubMed citations showed promise for the semi-automation of identification of Biomedical Literature.

Journal of clinical epidemiology
BACKGROUND AND OBJECTIVES: Systematic reviews form the basis of evidence-based medicine, but are expensive and time-consuming to produce. To address this burden, we have developed a literature identification system (Pythia) that combines the query fo...

Trust in Shared-Space Collaborative Robots: Shedding Light on the Human Brain.

Human factors
BACKGROUND: Industry 4.0 is currently underway allowing for improved manufacturing processes that leverage the collective advantages of human and robot agents. Consideration of trust can improve the quality and safety in such shared-space human-robot...