AIMC Topic: Diagnosis, Differential
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Discriminating progressive supranuclear palsy from Parkinson's disease using wearable technology and machine learning.
Gait & posture
Feb 10, 2020
BACKGROUND: Progressive supranuclear palsy (PSP), a neurodegenerative conditions may be difficult to discriminate clinically from idiopathic Parkinson's disease (PD). It is critical that we are able to do this accurately and as early as possible in o...
Automated differentiation of benign renal oncocytoma and chromophobe renal cell carcinoma on computed tomography using deep learning.
BJU international
Feb 6, 2020
OBJECTIVES: To develop and evaluate the feasibility of an objective method using artificial intelligence (AI) and image processing in a semi-automated fashion for tumour-to-cortex peak early-phase enhancement ratio (PEER) in order to differentiate CD...
A quantitative model based on clinically relevant MRI features differentiates lower grade gliomas and glioblastoma.
European radiology
Feb 5, 2020
OBJECTIVES: To establish a quantitative MR model that uses clinically relevant features of tumor location and tumor volume to differentiate lower grade glioma (LRGG, grades II and III) and glioblastoma (GBM, grade IV).
Automatic diagnosis for thyroid nodules in ultrasound images by deep neural networks.
Medical image analysis
Feb 4, 2020
Thyroid cancer is a disease in which the first symptom is a nodule in the thyroid region of the neck. It is one of the cancers with the highest incidences, and has the highest increase rate in the last thirty years. Ultrasonography is one of the most...
A machine learning approach for differentiating malignant from benign enhancing foci on breast MRI.
European radiology experimental
Jan 28, 2020
BACKGROUND: Differentiate malignant from benign enhancing foci on breast magnetic resonance imaging (MRI) through radiomic signature.
A Novel Deep Learning Approach with a 3D Convolutional Ladder Network for Differential Diagnosis of Idiopathic Normal Pressure Hydrocephalus and Alzheimer's Disease.
Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine
Jan 22, 2020
PURPOSE: Idiopathic normal pressure hydrocephalus (iNPH) and Alzheimer's disease (AD) are geriatric diseases and common causes of dementia. Recently, many studies on the segmentation, disease detection, or classification of MRI using deep learning ha...
Disease Progression
Case-Control Studies
Diagnosis, Computer-Assisted
Deep Learning
Imaging, Three-Dimensional
Image Processing, Computer-Assisted
Magnetic Resonance Imaging
Diagnosis, Differential
Aged
Aged, 80 and over
Male
Middle Aged
Artificial Intelligence
Brain
Female
Reproducibility of Results
Humans
Alzheimer Disease
Pattern Recognition, Automated
Neuroimaging
Hydrocephalus, Normal Pressure
Deep Learning to Distinguish Benign from Malignant Renal Lesions Based on Routine MR Imaging.
Clinical cancer research : an official journal of the American Association for Cancer Research
Jan 14, 2020
PURPOSE: With increasing incidence of renal mass, it is important to make a pretreatment differentiation between benign renal mass and malignant tumor. We aimed to develop a deep learning model that distinguishes benign renal tumors from renal cell c...
Differentiation of Small (≤ 4 cm) Renal Masses on Multiphase Contrast-Enhanced CT by Deep Learning.
AJR. American journal of roentgenology
Jan 8, 2020
This study evaluated the utility of a deep learning method for determining whether a small (≤ 4 cm) solid renal mass was benign or malignant on multiphase contrast-enhanced CT. This retrospective study included 1807 image sets from 168 pathological...
Editorial on "Diagnosis of Benign and Malignant Breast Lesions on DCE-MRI by Using Radiomics and Deep Learning With Consideration of Peritumor Tissue".
Journal of magnetic resonance imaging : JMRI
Dec 17, 2019
Utilizing Machine Learning for Image Quality Assessment for Reflectance Confocal Microscopy.
The Journal of investigative dermatology
Dec 12, 2019
In vivo reflectance confocal microscopy (RCM) enables clinicians to examine lesions' morphological and cytological information in epidermal and dermal layers while reducing the need for biopsies. As RCM is being adopted more widely, the workflow is e...
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