AIMC Topic: Algorithms

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FLANNEL (Focal Loss bAsed Neural Network EnsembLe) for COVID-19 detection.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: The study sought to test the possibility of differentiating chest x-ray images of coronavirus disease 2019 (COVID-19) against other pneumonia and healthy patients using deep neural networks.

[Prediction of epilepsy based on common spatial model algorithm and support vector machine double classification].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
At present the prediction method of epilepsy patients is very time-consuming and vulnerable to subjective factors, so this paper presented an automatic recognition method of epilepsy electroencephalogram (EEG) based on common spatial model (CSP) and ...

[A deep learning-based lung nodule density classification and segmentation method and its effectiveness under different CT reconstruction algorithms].

Zhonghua yi xue za zhi
To evaluate the diagnostic value of the lung nodule classification and segmentation algorithm based on deep learning among different CT reconstruction algorithms. Chest CT of 363 patients from June 2019 to September 2019 in Radiology Department of ...

[Analysis of pancreatic segmentation algorithm based on deep learning to improve pancreatic critical region segmentation ability on dual-phase CT].

Zhonghua yi xue za zhi
To investigate the segmentation effects of the deep learning method on CT in the arterial phase and venous phase respectively by using subjective and objective evaluation system, and to investigate the factors that affect the difference between arte...

Prediction of age and sex from paranasal sinus images using a deep learning network.

Medicine
This study was conducted to develop a convolutional neural network (CNN)-based model to predict the sex and age of patients by identifying unique unknown features from paranasal sinus (PNS) X-ray images.We employed a retrospective study design and us...

A machine-learning based approach to quantify fine crackles in the diagnosis of interstitial pneumonia: A proof-of-concept study.

Medicine
Fine crackles are frequently heard in patients with interstitial lung diseases (ILDs) and are known as the sensitive indicator for ILDs, although the objective method for analyzing respiratory sounds including fine crackles is not clinically availabl...

Machine learning for enzyme engineering, selection and design.

Protein engineering, design & selection : PEDS
Machine learning is a useful computational tool for large and complex tasks such as those in the field of enzyme engineering, selection and design. In this review, we examine enzyme-related applications of machine learning. We start by comparing tool...

[Overview of machine learning and its application in the management of emergency services].

Revista medica de Chile
The processes associated with health care generate a large amount of information that is difficult to analyze using standard statistical procedures. In this context, disciplines such as Data Science became relevant, mainly through strategies such as ...

Prediction of impacts on liver enzymes from the exposure of low-dose medical radiations through artificial intelligence algorithms.

Revista da Associacao Medica Brasileira (1992)
OBJECTIVES: This study aimed to develop artificial intelligence and machine learning-based models to predict alterations in liver enzymes from the exposure of low annual average effective doses in radiology and nuclear medicine personnel of Institute...

[Artificial intelligence: the inscrutability of algorithms.].

Recenti progressi in medicina
The use of artificial intelligence radically changes the role of the doctor and his/her relationship with the patient, which becomes in fact a three-way relationship: artificial intelligence-doctor-patient, in which the first component is able to hea...