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Automation

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Improvement of intervention information detection for automated clinical literature screening during systematic review.

Journal of biomedical informatics
Systematic literature review (SLR) is a crucial method for clinicians and policymakers to make their decisions in a flood of new clinical studies. Because manual literature screening in SLR is a highly laborious task, its automation by natural langua...

Inspecting Decorative Ceramic Defects by Fusing Convolutional Neural Network and Image Recognition.

Computational intelligence and neuroscience
The intelligent inspection of ceramic decorative defects is one of the hot research at present. This work aims to improve the defect inspection automation of finished decorative ceramic workpieces. First, it introduces the multi-target detection algo...

Abnormality classification and localization using dual-branch whole-region-based CNN model with histopathological images.

Computers in biology and medicine
The task of classification and localization with detecting abnormalities in medical images is considered very challenging. Computer-aided systems have been widely employed to address this issue, and the proliferation of deep learning network architec...

Human-Robot Collaboration in Industrial Automation: Sensors and Algorithms.

Sensors (Basel, Switzerland)
Technology is changing the manufacturing world [...].

Automation in ART: Paving the Way for the Future of Infertility Treatment.

Reproductive sciences (Thousand Oaks, Calif.)
In vitro fertilisation (IVF) is estimated to account for the birth of more than nine million babies worldwide, perhaps making it one of the most intriguing as well as commoditised and industrialised modern medical interventions. Nevertheless, most IV...

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...