AIMC Topic: Aged, 80 and over
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Intensity harmonization techniques influence radiomics features and radiomics-based predictions in sarcoma patients.
Scientific reports
Sep 23, 2020
Intensity harmonization techniques (IHT) are mandatory to homogenize multicentric MRIs before any quantitative analysis because signal intensities (SI) do not have standardized units. Radiomics combine quantification of tumors' radiological phenotype...
Alcoholic liver disease: A registry view on comorbidities and disease prediction.
PLoS computational biology
Sep 22, 2020
Alcoholic-related liver disease (ALD) is the cause of more than half of all liver-related deaths. Sustained excess drinking causes fatty liver and alcohol-related steatohepatitis, which may progress to alcoholic liver fibrosis (ALF) and eventually to...
Classifications of Neurodegenerative Disorders Using a Multiplex Blood Biomarkers-Based Machine Learning Model.
International journal of molecular sciences
Sep 21, 2020
Easily accessible biomarkers for Alzheimer's disease (AD), Parkinson's disease (PD), frontotemporal dementia (FTD), and related neurodegenerative disorders are urgently needed in an aging society to assist early-stage diagnoses. In this study, we aim...
Influence of medical domain knowledge on deep learning for Alzheimer's disease prediction.
Computer methods and programs in biomedicine
Sep 20, 2020
BACKGROUND AND OBJECTIVE: Alzheimer's disease (AD) is the most common type of dementia that can seriously affect a person's ability to perform daily activities. Estimates indicate that AD may rank third as a cause of death for older people, after hea...
Artificial Intelligence ECG to Detect Left Ventricular Dysfunction in COVID-19: A Case Series.
Mayo Clinic proceedings
Sep 19, 2020
Coronavirus disease 2019 (COVID-19) can result in deterioration of cardiac function, which is associated with high mortality. A simple point-of-care diagnostic test to screen for ventricular dysfunction would be clinically useful to guide management....
Accuracy of Artificial Intelligence Formulas and Axial Length Adjustments for Highly Myopic Eyes.
American journal of ophthalmology
Sep 18, 2020
PURPOSE: To compare the accuracy of artificial intelligence formulas (Kane formula and Radial Basis Function [RBF] 2.0) and other formulas, including the original and modified Wang-Koch (MWK) adjustment formulas for Holladay 1 (H1-MWK) and SRK/T (SRK...
Prediction of early recurrence of hepatocellular carcinoma after resection using digital pathology images assessed by machine learning.
Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc
Sep 18, 2020
Hepatocellular carcinoma (HCC) is a representative primary liver cancer caused by long-term and repetitive liver injury. Surgical resection is generally selected as the radical cure treatment. Because the early recurrence of HCC after resection is as...
Electroencephalography Might Improve Diagnosis of Acute Stroke and Large Vessel Occlusion.
Stroke
Sep 18, 2020
BACKGROUND AND PURPOSE: Clinical methods have incomplete diagnostic value for early diagnosis of acute stroke and large vessel occlusion (LVO). Electroencephalography is rapidly sensitive to brain ischemia. This study examined the diagnostic utility ...
Convolutional neural networks versus radiologists in characterization of small hypoattenuating hepatic nodules on CT: a critical diagnostic challenge in staging of colorectal carcinoma.
Scientific reports
Sep 17, 2020
Our objective was to compare the diagnostic performance and diagnostic confidence of convolutional neural networks (CNN) to radiologists in characterizing small hypoattenuating hepatic nodules (SHHN) in colorectal carcinoma (CRC) on CT scans. Retrosp...
Radiologists
Radiographic Image Interpretation, Computer-Assisted
Observer Variation
Expert Testimony
Aged, 80 and over
Neural Networks, Computer
Young Adult
Retrospective Studies
Adult
Tomography, X-Ray Computed
Colorectal Neoplasms
Female
Male
Aged
Middle Aged
Diagnosis, Computer-Assisted
Humans
Liver Neoplasms
Liver
Neoplasm Staging
Increasing tendency of urine protein is a risk factor for rapid eGFR decline in patients with CKD: A machine learning-based prediction model by using a big database.
PloS one
Sep 17, 2020
Artificial intelligence is increasingly being adopted in medical fields to predict various outcomes. In particular, chronic kidney disease (CKD) is problematic because it often progresses to end-stage kidney disease. However, the trajectories of kidn...
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