AIMC Topic: Female

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Deep learning reconstruction improves image quality of abdominal ultra-high-resolution CT.

European radiology
OBJECTIVES: Deep learning reconstruction (DLR) is a new reconstruction method; it introduces deep convolutional neural networks into the reconstruction flow. This study was conducted in order to examine the clinical applicability of abdominal ultra-h...

Prognostic Value of Deep Learning PET/CT-Based Radiomics: Potential Role for Future Individual Induction Chemotherapy in Advanced Nasopharyngeal Carcinoma.

Clinical cancer research : an official journal of the American Association for Cancer Research
PURPOSE: We aimed to evaluate the value of deep learning on positron emission tomography with computed tomography (PET/CT)-based radiomics for individual induction chemotherapy (IC) in advanced nasopharyngeal carcinoma (NPC).

Predicting daily outcomes in acetaminophen-induced acute liver failure patients with machine learning techniques.

Computer methods and programs in biomedicine
BACKGROUND/OBJECTIVE: Assessing prognosis for acetaminophen-induced acute liver failure (APAP-ALF) patients during the first week of hospitalization often presents significant challenges. Current models such as the King's College Criteria (KCC) and t...

Differential diagnosis of multiple system atrophy with predominant parkinsonism and Parkinson's disease using neural networks.

Journal of the neurological sciences
Differential diagnosis between Parkinson's disease (PD) and atypical parkinsonism, such as multiple system atrophy (MSA), can be difficult, especially in the early stages of the disease. Deep learning using neural networks (NNs) makes possible the pr...

Assaying neural activity of children during video game play in public spaces: a deep learning approach.

Journal of neural engineering
OBJECTIVE: Understanding neural activity patterns in the developing brain remains one of the grand challenges in neuroscience. Developing neural networks are likely to be endowed with functionally important variability associated with the environment...

Application of Artificial Intelligence for Preoperative Diagnostic and Prognostic Prediction in Epithelial Ovarian Cancer Based on Blood Biomarkers.

Clinical cancer research : an official journal of the American Association for Cancer Research
PURPOSE: We aimed to develop an ovarian cancer-specific predictive framework for clinical stage, histotype, residual tumor burden, and prognosis using machine learning methods based on multiple biomarkers.

Hand Extension Robot Orthosis (HERO) Glove: Development and Testing With Stroke Survivors With Severe Hand Impairment.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
The hand extension robot orthosis (HERO) glove was iteratively designed with occupational therapists and stroke survivors to enable stroke survivors with severe hand impairment to grasp and stabilize everyday objects, while being portable, lightweigh...

Application of Artificial Neural Networks to Identify Alzheimer's Disease Using Cerebral Perfusion SPECT Data.

International journal of environmental research and public health
The aim of this study was to demonstrate the usefulness of artificial neural networks in Alzheimer disease diagnosis (AD) using data of brain single photon emission computed tomography (SPECT). The results were compared with discriminant analysis. Th...

Feasible Classified Models for Parkinson Disease from Tc-TRODAT-1 SPECT Imaging.

Sensors (Basel, Switzerland)
The neuroimaging techniques such as dopaminergic imaging using Single Photon Emission Computed Tomography (SPECT) with Tc-TRODAT-1 have been employed to detect the stages of Parkinson's disease (PD). In this retrospective study, a total of 202 Tc-TRO...