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Early Diagnosis

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PredyCLU: A prediction system for chronic leg ulcers based on fuzzy logic; part II-Exploring the arterial side.

International wound journal
Peripheral arterial disease (PAD) and its most severe form, critical limb ischaemia (CLI), are very common clinical conditions related to atherosclerosis and represent the major causes of morbidity, mortality, disability, and reduced quality of life ...

Deep Learning-Based Algorithm for Detecting Aortic Stenosis Using Electrocardiography.

Journal of the American Heart Association
Background Severe, symptomatic aortic stenosis (AS) is associated with poor prognoses. However, early detection of AS is difficult because of the long asymptomatic period experienced by many patients, during which screening tools are ineffective. The...

Identification of COVID-19 can be quicker through artificial intelligence framework using a mobile phone-based survey when cities and towns are under quarantine.

Infection control and hospital epidemiology
We propose the use of a machine learning algorithm to improve possible COVID-19 case identification more quickly using a mobile phone-based web survey. This method could reduce the spread of the virus in susceptible populations under quarantine.

A novel CNN based Alzheimer's disease classification using hybrid enhanced ICA segmented gray matter of MRI.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Predicting Alzheimer's Disease (AD) from Mild Cognitive Impairment (MCI) and Cognitive Normal (CN) has become wide. Recent advancement in neuroimaging in adoption with machine learning techniques are especially useful for pattern recognition of medic...

DMENet: Diabetic Macular Edema diagnosis using Hierarchical Ensemble of CNNs.

PloS one
UNLABELLED: Diabetic Macular Edema (DME) is an advanced stage of Diabetic Retinopathy (DR) and can lead to permanent vision loss. Currently, it affects 26.7 million people globally and on account of such a huge number of DME cases and the limited num...

Effect of a deep-learning computer-aided detection system on adenoma detection during colonoscopy (CADe-DB trial): a double-blind randomised study.

The lancet. Gastroenterology & hepatology
BACKGROUND: Colonoscopy with computer-aided detection (CADe) has been shown in non-blinded trials to improve detection of colon polyps and adenomas by providing visual alarms during the procedure. We aimed to assess the effectiveness of a CADe system...

Self-calibrated brain network estimation and joint non-convex multi-task learning for identification of early Alzheimer's disease.

Medical image analysis
Detection of early stages of Alzheimer's disease (AD) (i.e., mild cognitive impairment (MCI)) is important to maximize the chances to delay or prevent progression to AD. Brain connectivity networks inferred from medical imaging data have been commonl...

Adaptive sparse learning using multi-template for neurodegenerative disease diagnosis.

Medical image analysis
Neurodegenerative diseases are excessively affecting millions of patients, especially elderly people. Early detection and management of these diseases are crucial as the clinical symptoms take years to appear after the onset of neuro-degeneration. Th...

A novel computer-aided diagnosis system for the early detection of hypertension based on cerebrovascular alterations.

NeuroImage. Clinical
Hypertension is a leading cause of mortality in the USA. While simple tools such as the sphygmomanometer are widely used to diagnose hypertension, they could not predict the disease before its onset. Clinical studies suggest that alterations in the s...

Self-attention based recurrent convolutional neural network for disease prediction using healthcare data.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Nowadays computer-aided disease diagnosis from medical data through deep learning methods has become a wide area of research. Existing works of analyzing clinical text data in the medical domain, which substantiate useful in...