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Early Diagnosis

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Prediction and early detection of delirium in the intensive care unit by using heart rate variability and machine learning.

Physiological measurement
OBJECTIVE: Delirium is an important syndrome found in patients in the intensive care unit (ICU), however, it is usually under-recognized during treatment. This study was performed to investigate whether delirious patients can be successfully distingu...

Predicting urinary tract infections in the emergency department with machine learning.

PloS one
BACKGROUND: Urinary tract infection (UTI) is a common emergency department (ED) diagnosis with reported high diagnostic error rates. Because a urine culture, part of the gold standard for diagnosis of UTI, is usually not available for 24-48 hours aft...

Multiscale deep neural network based analysis of FDG-PET images for the early diagnosis of Alzheimer's disease.

Medical image analysis
Alzheimer's disease (AD) is one of the most common neurodegenerative diseases with a commonly seen prodromal mild cognitive impairment (MCI) phase where memory loss is the main complaint progressively worsening with behavior issues and poor self-care...

Predicting non-melanoma skin cancer via a multi-parameterized artificial neural network.

Scientific reports
Ultraviolet radiation (UVR) exposure and family history are major associated risk factors for the development of non-melanoma skin cancer (NMSC). The objective of this study was to develop and validate a multi-parameterized artificial neural network ...

A novel method for predicting kidney stone type using ensemble learning.

Artificial intelligence in medicine
The high morbidity rate associated with kidney stone disease, which is a silent killer, is one of the main concerns in healthcare systems all over the world. Advanced data mining techniques such as classification can help in the early prediction of t...

Early Diagnosis of Alzheimer's Disease Based on Resting-State Brain Networks and Deep Learning.

IEEE/ACM transactions on computational biology and bioinformatics
Computerized healthcare has undergone rapid development thanks to the advances in medical imaging and machine learning technologies. Especially, recent progress on deep learning opens a new era for multimedia based clinical decision support. In this ...

A Diadochokinesis-based expert system considering articulatory features of plosive consonants for early detection of Parkinson's disease.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: A new expert system is proposed to discriminate healthy people from people with Parkinson's Disease (PD) in early stages by using Diadochokinesis tests.

Ensemble based on static classifier selection for automated diagnosis of Mild Cognitive Impairment.

Journal of neuroscience methods
BACKGROUND: Alzheimer's disease (AD) is the most common cause of neurodegenerative dementia in the elderly population. Scientific research is very active in the challenge of designing automated approaches to achieve an early and certain diagnosis. Re...

Early Detection of Ureteropelvic Junction Obstruction Using Signal Analysis and Machine Learning: A Dynamic Solution to a Dynamic Problem.

The Journal of urology
PURPOSE: We sought to define features that describe the dynamic information in diuresis renograms for the early detection of clinically significant hydronephrosis caused by ureteropelvic junction obstruction.