AIMC Topic: Humans

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Inferring pediatric knee skeletal maturity from MRI using deep learning.

Skeletal radiology
PURPOSE: Many children who undergo MR of the knee to evaluate traumatic injury may not undergo a separate dedicated evaluation of their skeletal maturity, and we wished to investigate how accurately skeletal maturity could be automatically inferred f...

Deep learning identifies brain structures that predict cognition and explain heterogeneity in cognitive aging.

NeuroImage
Specific brain structures (gray matter regions and white matter tracts) play a dominant role in determining cognitive decline and explain the heterogeneity in cognitive aging. Identification of these structures is crucial for screening of older adult...

Human Being Detection from UWB NLOS Signals: Accuracy and Generality of Advanced Machine Learning Models.

Sensors (Basel, Switzerland)
This paper studies the problem of detecting human beings in non-line-of-sight (NLOS) conditions using an ultra-wideband radar. We perform an extensive measurement campaign in realistic environments, considering different body orientations, the obstac...

Near-Infrared Spectral Characteristic Extraction and Qualitative Analysis Method for Complex Multi-Component Mixtures Based on TRPCA-SVM.

Sensors (Basel, Switzerland)
Quality identification of multi-component mixtures is essential for production process control. Artificial sensory evaluation is a conventional quality evaluation method of multi-component mixture, which is easily affected by human subjective factors...

Artificial intelligence in mammographic phenotyping of breast cancer risk: a narrative review.

Breast cancer research : BCR
BACKGROUND: Improved breast cancer risk assessment models are needed to enable personalized screening strategies that achieve better harm-to-benefit ratio based on earlier detection and better breast cancer outcomes than existing screening guidelines...

Machine Learning-Based Cry Diagnostic System for Identifying Septic Newborns.

Journal of voice : official journal of the Voice Foundation
BACKGROUND AND OBJECTIVE: Processing the newborns' cry audio signal (CAS) provides valuable information about the newborns' condition. This information can be used to diagnose the disease. This article analyzes the CASs of newborns under two months o...

IoT-based automated water pollution treatment using machine learning classifiers.

Environmental technology
Water is one of the most vital sources for the survival of life. In the globe, the accessibility of water in safe and healthy ways is a major concern. The consumption of unsafe water may lead to health risks. Therefore, it is necessary to classify an...

A comparison of laparoscopic and robotic ergonomic risk.

Surgical endoscopy
INTRODUCTION: Work related injuries in minimally invasive surgery (MIS) are common because of the strains placed on the surgeon's or assistant's body. The objective of this study was to compare specific ergonomic risks among surgeons and surgical tra...

Accelerating susceptibility-weighted imaging with deep learning by complex-valued convolutional neural network (ComplexNet): validation in clinical brain imaging.

European radiology
OBJECTIVES: Susceptibility-weighted imaging (SWI) is crucial for the characterization of intracranial hemorrhage and mineralization, but has the drawback of long acquisition times. We aimed to propose a deep learning model to accelerate SWI, and eval...