AIMC Topic: Humans

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Validation of a Predictive Model for New Baseline Renal Function After Radical Nephrectomy or Robot-Assisted Partial Nephrectomy in Japanese Patients.

Journal of endourology
The study's aim was to externally validate a new predictive model for the new baseline glomerular filtration rate (NB-GFR) postnephrectomy among Japanese patients. Patients with renal tumors who underwent radical nephrectomy (RN) or robot-assisted ...

WBC image classification and generative models based on convolutional neural network.

BMC medical imaging
BACKGROUND: Computer-aided methods for analyzing white blood cells (WBC) are popular due to the complexity of the manual alternatives. Recent works have shown highly accurate segmentation and detection of white blood cells from microscopic blood imag...

Machine learning phenomics (MLP) combining deep learning with time-lapse-microscopy for monitoring colorectal adenocarcinoma cells gene expression and drug-response.

Scientific reports
High-throughput phenotyping is becoming increasingly available thanks to analytical and bioinformatics approaches that enable the use of very high-dimensional data and to the availability of dynamic models that link phenomena across levels: from gene...

Evaluating machine learning classifiers for glaucoma referral decision support in primary care settings.

Scientific reports
Several artificial intelligence algorithms have been proposed to help diagnose glaucoma by analyzing the functional and/or structural changes in the eye. These algorithms require carefully curated datasets with access to ocular images. In the current...

A pediatric wrist trauma X-ray dataset (GRAZPEDWRI-DX) for machine learning.

Scientific data
Digital radiography is widely available and the standard modality in trauma imaging, often enabling to diagnose pediatric wrist fractures. However, image interpretation requires time-consuming specialized training. Due to astonishing progress in comp...

A Modified ResNeXt for Android Malware Identification and Classification.

Computational intelligence and neuroscience
It is critical to successfully identify, mitigate, and fight against Android malware assaults, since Android malware has long been a significant threat to the security of Android applications. Identifying and categorizing dangerous applications into ...

Efficient 3D AlexNet Architecture for Object Recognition Using Syntactic Patterns from Medical Images.

Computational intelligence and neuroscience
In computer vision and medical image processing, object recognition is the primary concern today. Humans require only a few milliseconds for object recognition and visual stimulation. This led to the development of a computer-specific pattern recogni...

Film Effect Optimization by Deep Learning and Virtual Reality Technology in New Media Environment.

Computational intelligence and neuroscience
Today, new media technology has widely penetrated art forms such as film and television, which has changed the way of visual expression in the new media environment. To better solve the problems of weak immersion, poor interaction, and low degree of ...

The perspectives of older adults with mild cognitive impairment and their caregivers on the use of socially assistive robots in healthcare: exploring factors that influence attitude in a pre-implementation stage.

Disability and rehabilitation. Assistive technology
BACKGROUND: Due to increasing age and an increasing prevalence rate of neurocognitive disorders such as Mild Cognitive Impairment (MCI) and dementia, independent living may become challenging. The use of socially assistive robots (SARs) is one soluti...

Machine Learning for The Prediction of Ranked Applicants and Matriculants to an Internal Medicine Residency Program.

Teaching and learning in medicine
: Residency programs throughout the country each receive hundreds to thousands of applications every year. Holistic review of this many applications is challenging, and to-date, few tools exist to streamline or assist in the process for selecting can...