AIMC Topic: Automation

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Deep vector-based convolutional neural network approach for automatic recognition of colonies of induced pluripotent stem cells.

PloS one
Pluripotent stem cells can potentially be used in clinical applications as a model for studying disease progress. This tracking of disease-causing events in cells requires constant assessment of the quality of stem cells. Existing approaches are inad...

Automatic Detection of Acromegaly From Facial Photographs Using Machine Learning Methods.

EBioMedicine
BACKGROUND: Automatic early detection of acromegaly is theoretically possible from facial photographs, which can lessen the prevalence and increase the cure probability.

A novel fully automatic multilevel thresholding technique based on optimized intuitionistic fuzzy sets and tsallis entropy for MR brain tumor image segmentation.

Australasian physical & engineering sciences in medicine
In the present paper, a hybrid multilevel thresholding technique that combines intuitionistic fuzzy sets and tsallis entropy has been proposed for the automatic delineation of the tumor from magnetic resonance images having vague boundaries and poor ...

An EEG-based functional connectivity measure for automatic detection of alcohol use disorder.

Artificial intelligence in medicine
BACKGROUND: The abnormal alcohol consumption could cause toxicity and could alter the human brain's structure and function, termed as alcohol used disorder (AUD). Unfortunately, the conventional screening methods for AUD patients are subjective and m...

Automatic diagnosis of imbalanced ophthalmic images using a cost-sensitive deep convolutional neural network.

Biomedical engineering online
BACKGROUND: Ocular images play an essential role in ophthalmological diagnoses. Having an imbalanced dataset is an inevitable issue in automated ocular diseases diagnosis; the scarcity of positive samples always tends to result in the misdiagnosis of...

Deep reinforcement learning for automated radiation adaptation in lung cancer.

Medical physics
PURPOSE: To investigate deep reinforcement learning (DRL) based on historical treatment plans for developing automated radiation adaptation protocols for nonsmall cell lung cancer (NSCLC) patients that aim to maximize tumor local control at reduced r...

Self-Driving Cars and Engineering Ethics: The Need for a System Level Analysis.

Science and engineering ethics
The literature on self-driving cars and ethics continues to grow. Yet much of it focuses on ethical complexities emerging from an individual vehicle. That is an important but insufficient step towards determining how the technology will impact human ...

Surface electromyography based muscle fatigue detection using high-resolution time-frequency methods and machine learning algorithms.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Surface electromyography (sEMG) based muscle fatigue research is widely preferred in sports science and occupational/rehabilitation studies due to its noninvasiveness. However, these signals are complex, multicomponent and h...

MIAQuant, a novel system for automatic segmentation, measurement, and localization comparison of different biomarkers from serialized histological slices.

European journal of histochemistry : EJH
In the clinical practice, automatic image analysis methods quickly quantizing histological results by objective and replicable methods are getting more and more necessary and widespread. Despite several commercial software products are available for ...

High-accuracy automatic classification of Parkinsonian tremor severity using machine learning method.

Physiological measurement
MOTIVATION: Although clinical aspirations for new technology to accurately measure and diagnose Parkinsonian tremors exist, automatic scoring of tremor severity using machine learning approaches has not yet been employed.