AIMC Topic: Humans

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Unsupervised method for normalization of hematoxylin-eosin stain in histological images.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Histological images stained with hematoxylin-eosin are widely used by pathologists for cancer diagnosis. However, these images can have color variations that highly influence the histological image processing techniques. To deal with this potential l...

Multiscale brain MRI super-resolution using deep 3D convolutional networks.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
The purpose of super-resolution approaches is to overcome the hardware limitations and the clinical requirements of imaging procedures by reconstructing high-resolution images from low-resolution acquisitions using post-processing methods. Super-reso...

An interpretable natural language processing system for written medical examination assessment.

Journal of biomedical informatics
OBJECTIVE: The assessment of written medical examinations is a tedious and expensive process, requiring significant amounts of time from medical experts. Our objective was to develop a natural language processing (NLP) system that can expedite the as...

Performance of an artificial intelligence algorithm for reporting urine cytopathology.

Cancer cytopathology
BACKGROUND: Unlike Papanicolaou tests, there are no commercially available computer-assisted automated screening systems for urine specimens. Despite The Paris System for Reporting Urinary Cytology, there still is poor interobserver agreement with ur...

Assisted therapeutic system based on reinforcement learning for children with autism.

Computer assisted surgery (Abingdon, England)
Assisted therapy is increasingly used in autism spectrum disorders (ASD) for improving social interaction and communication skills in recent years. A lot of studies have proven that the form of interactive games for therapy has a good effect on child...

Systematic outperformance of 112 dermatologists in multiclass skin cancer image classification by convolutional neural networks.

European journal of cancer (Oxford, England : 1990)
BACKGROUND: Recently, convolutional neural networks (CNNs) systematically outperformed dermatologists in distinguishing dermoscopic melanoma and nevi images. However, such a binary classification does not reflect the clinical reality of skin cancer s...

Predicting Clinical Outcomes of Large Vessel Occlusion Before Mechanical Thrombectomy Using Machine Learning.

Stroke
Background and Purpose- The clinical course of acute ischemic stroke with large vessel occlusion (LVO) is a multifactorial process with various prognostic factors. We aimed to model this process with machine learning and predict the long-term clinica...

A controller for walking derived from how humans recover from perturbations.

Journal of the Royal Society, Interface
Humans can walk without falling despite some external perturbations, but the control mechanisms by which this stability is achieved have not been fully characterized. While numerous walking simulations and robots have been constructed, no full-state ...

Artificial intelligence predicts the progression of diabetic kidney disease using big data machine learning.

Scientific reports
Artificial intelligence (AI) is expected to support clinical judgement in medicine. We constructed a new predictive model for diabetic kidney diseases (DKD) using AI, processing natural language and longitudinal data with big data machine learning, b...