AIMC Topic: Humans

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Understanding sexual homicide in Korea using machine learning algorithms.

Behavioral sciences & the law
The current study was conducted to confirm the characteristics in sexual homicide and to explore variables that effectively differentiate sexual homicide and nonsexual homicide. Further, newer methods that have received attention in criminology, such...

Identification of novel biomarkers to distinguish clear cell and non-clear cell renal cell carcinoma using bioinformatics and machine learning.

PloS one
Renal cell carcinoma (RCC), accounting for 90% of all kidney cancer, is categorized into clear cell RCC (ccRCC) and non-clear cell RCC (non-ccRCC) for treatment based on the current NCCN Guidelines. Thus, the classification will be associated with th...

Recovering high-quality fiber orientation distributions from a reduced number of diffusion-weighted images using a model-driven deep learning architecture.

Magnetic resonance in medicine
PURPOSE: The aim of this study was to develop a model-based deep learning architecture to accurately reconstruct fiber orientation distributions (FODs) from a reduced number of diffusion-weighted images (DWIs), facilitating accurate analysis with red...

Enhanced parameter estimation in multiparametric arterial spin labeling using artificial neural networks.

Magnetic resonance in medicine
PURPOSE: Multiparametric arterial spin labeling (MP-ASL) can quantify cerebral blood flow (CBF) and arterial cerebral blood volume (CBV). However, its accuracy is compromised owing to its intrinsically low SNR, necessitating complex and time-consumin...

Exploring liquid-liquid phase separation-related diagnostic biomarkers in osteoarthritis based on machine learning algorithms and experiment.

Immunobiology
BACKGROUND: Osteoarthritis (OA) is a prevalent joint disorder characterized by cartilage degeneration and joint inflammation. Liquid-liquid phase separation (LLPS), a biophysical process involved in cellular organization, has recently gained attentio...

Automatic detection of the third molar and mandibular canal on panoramic radiographs based on deep learning.

Journal of stomatology, oral and maxillofacial surgery
PURPOSE: This study aims to develop a deep learning framework for the automatic detection of the position relationship between the mandibular third molar (M3) and the mandibular canal (MC) on panoramic radiographs (PRs), to assist doctors in assessin...

Revolutionizing breast cancer Ki-67 diagnosis: ultrasound radiomics and fully connected neural networks (FCNN) combination method.

Breast cancer research and treatment
PURPOSE: This study aims to assess the diagnostic value of ultrasound habitat sub-region radiomics feature parameters using a fully connected neural networks (FCNN) combination method L2,1-norm in relation to breast cancer Ki-67 status.

Partial class activation mapping guided graph convolution cascaded U-Net for retinal vessel segmentation.

Computers in biology and medicine
Accurate segmentation of retinal vessels in fundus images is of great importance for the diagnosis of numerous ocular diseases. However, due to the complex characteristics of fundus images, such as various lesions, image noise and complex background,...

HTC-retina: A hybrid retinal diseases classification model using transformer-Convolutional Neural Network from optical coherence tomography images.

Computers in biology and medicine
Retinal diseases are among nowadays major public health issues, deservedly needing advanced computer-aided diagnosis. We propose a hybrid model for multi label classification, whereby seven retinal diseases are automatically classified from Optical C...