AIMC Topic: Humans

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A convolutional deep learning model for improving mammographic breast-microcalcification diagnosis.

Scientific reports
This study aimed to assess the diagnostic performance of deep convolutional neural networks (DCNNs) in classifying breast microcalcification in screening mammograms. To this end, 1579 mammographic images were collected retrospectively from patients e...

A machine and human reader study on AI diagnosis model safety under attacks of adversarial images.

Nature communications
While active efforts are advancing medical artificial intelligence (AI) model development and clinical translation, safety issues of the AI models emerge, but little research has been done. We perform a study to investigate the behaviors of an AI dia...

Proof of concept and development of a couple-based machine learning model to stratify infertile patients with idiopathic infertility.

Scientific reports
We aimed to develop and evaluate a machine learning model that can stratify infertile/fertile couples on the basis of their bioclinical signature helping the management of couples with unexplained infertility. Fertile and infertile couples were recru...

Training a deep learning model for single-cell segmentation without manual annotation.

Scientific reports
Advances in the artificial neural network have made machine learning techniques increasingly more important in image analysis tasks. Recently, convolutional neural networks (CNN) have been applied to the problem of cell segmentation from microscopy i...

Integrated linkage-driven dexterous anthropomorphic robotic hand.

Nature communications
Robotic hands perform several amazing functions similar to the human hands, thereby offering high flexibility in terms of the tasks performed. However, developing integrated hands without additional actuation parts while maintaining important functio...

Deep neural network models reveal interplay of peripheral coding and stimulus statistics in pitch perception.

Nature communications
Perception is thought to be shaped by the environments for which organisms are optimized. These influences are difficult to test in biological organisms but may be revealed by machine perceptual systems optimized under different conditions. We invest...

Integrated Multiomics Analysis Identifies a Novel Biomarker Associated with Prognosis in Intracerebral Hemorrhage.

Oxidative medicine and cellular longevity
Existing treatments for intracerebral hemorrhage (ICH) are unable to satisfactorily prevent development of secondary brain injury after ICH and multiple pathological mechanisms are involved in the development of the injury. In this study, we aimed to...

Ensemble of EfficientNets for the Diagnosis of Tuberculosis.

Computational intelligence and neuroscience
Tuberculosis (TB) remains a life-threatening disease and is one of the leading causes of mortality in developing regions due to poverty and inadequate medical resources. Tuberculosis is medicable, but it necessitates early diagnosis through reliable ...

Malicious Code Variant Identification Based on Multiscale Feature Fusion CNNs.

Computational intelligence and neuroscience
The increasing volume and types of malwares bring a great threat to network security. The malware binary detection with deep convolutional neural networks (CNNs) has been proved to be an effective method. However, the existing malware classification ...

Machine learning-based patient classification system for adults with stroke: A systematic review.

Chronic illness
OBJECTIVE: To evaluate the existing evidence of a machine learning-based classification system that stratifies patients with stroke.