AIMC Topic: Early Diagnosis

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Development and Validation of a Deep Learning Model for Earlier Detection of Cognitive Decline From Clinical Notes in Electronic Health Records.

JAMA network open
IMPORTANCE: Detecting cognitive decline earlier among older adults can facilitate enrollment in clinical trials and early interventions. Clinical notes in longitudinal electronic health records (EHRs) provide opportunities to detect cognitive decline...

Applying artificial neural network for early detection of sepsis with intentionally preserved highly missing real-world data for simulating clinical situation.

BMC medical informatics and decision making
PURPOSE: Some predictive systems using machine learning models have been developed to predict sepsis; however, they were mostly built with a low percent of missing values, which does not correspond with the actual clinical situation. In this study, w...

Automated Diagnosis of Chest X-Ray for Early Detection of COVID-19 Disease.

Computational and mathematical methods in medicine
In March 2020, the World Health Organization announced the COVID-19 pandemic, its dangers, and its rapid spread throughout the world. In March 2021, the second wave of the pandemic began with a new strain of COVID-19, which was more dangerous for som...

Classification of Alzheimer's Disease Using Gaussian-Based Bayesian Parameter Optimization for Deep Convolutional LSTM Network.

Computational and mathematical methods in medicine
Alzheimer's disease (AD) is one of the most important causes of mortality in elderly people, and it is often challenging to use traditional manual procedures when diagnosing a disease in the early stages. The successful implementation of machine lear...

A Machine Learning Model for Evaluating Imported Disease Screening Strategies in Immigrant Populations.

The American journal of tropical medicine and hygiene
Given the high prevalence of imported diseases in immigrant populations, it has postulated the need to establish screening programs that allow their early diagnosis and treatment. We present a mathematical model based on machine learning methodologie...

Deep Learning-Based Image Feature with Arthroscopy-Aided Early Diagnosis and Treatment of Meniscus Injury of Knee Joint.

Journal of healthcare engineering
The aim of this study is to explore the clinical effect of deep learning-based MRI-assisted arthroscopy in the early treatment of knee meniscus sports injury. Based on convolutional neural network algorithm, Adam algorithm was introduced to optimize ...

Predicting clinical outcomes in COVID-19 using radiomics on chest radiographs.

The British journal of radiology
OBJECTIVES: For optimal utilization of healthcare resources, there is a critical need for early identification of COVID-19 patients at risk of poor prognosis as defined by the need for intensive unit care and mechanical ventilation. We tested the fea...

Staged reflexive artificial intelligence driven testing algorithms for early diagnosis of pituitary disorders.

Clinical biochemistry
BACKGROUND: Sellar masses (SM) frequently present with insidious hormonal dysfunction. We previously showed that, by utilizing a combined reflex/reflecting approach involving a laboratory clinician (LC) on common endocrine test results requested by n...

Chronic kidney disease diagnosis using decision tree algorithms.

BMC nephrology
BACKGROUND: Chronic Kidney Disease (CKD), i.e., gradual decrease in the renal function spanning over a duration of several months to years without any major symptoms, is a life-threatening disease. It progresses in six stages according to the severit...