AIMC Topic: Reproducibility of Results

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Augmentation of Transcriptomic Data for Improved Classification of Patients with Respiratory Diseases of Viral Origin.

International journal of molecular sciences
To better understand the molecular basis of respiratory diseases of viral origin, high-throughput gene-expression data are frequently taken by means of DNA microarray or RNA-seq technology. Such data can also be useful to classify infected individual...

Artificial intelligence-based classification of bone tumors in the proximal femur on plain radiographs: System development and validation.

PloS one
PURPOSE: Early detection and classification of bone tumors in the proximal femur is crucial for their successful treatment. This study aimed to develop an artificial intelligence (AI) model to classify bone tumors in the proximal femur on plain radio...

MIXTURE of human expertise and deep learning-developing an explainable model for predicting pathological diagnosis and survival in patients with interstitial lung disease.

Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc
Interstitial pneumonia is a heterogeneous disease with a progressive course and poor prognosis, at times even worse than those in the main cancer types. Histopathological examination is crucial for its diagnosis and estimation of prognosis. However, ...

Reproducible neuroimaging features for diagnosis of autism spectrum disorder with machine learning.

Scientific reports
Autism spectrum disorder (ASD) is the fourth most common neurodevelopmental disorder, with a prevalence of 1 in 160 children. Accurate diagnosis relies on experts, but such individuals are scarce. This has led to increasing interest in the developmen...

Deep learning identifies Acute Promyelocytic Leukemia in bone marrow smears.

BMC cancer
BACKGROUND: Acute promyelocytic leukemia (APL) is considered a hematologic emergency due to high risk of bleeding and fatal hemorrhages being a major cause of death. Despite lower death rates reported from clinical trials, patient registry data sugge...

A computational framework to solve the nonlinear dengue fever SIR system.

Computer methods in biomechanics and biomedical engineering
This study is relevant to present the numerical form of the nonlinear dengue fever SIR system are presented using the artificial neural networks along with the Levenberg-Marquardt backpropagation technique, i.e. ANNs-LMB. The procedures of ANNs-LMB a...

Significance of Visible Non-Invasive Risk Attributes for the Initial Prediction of Heart Disease Using Different Machine Learning Techniques.

Computational intelligence and neuroscience
INTRODUCTION: Heart disease is emerging as the single most critical cause of death worldwide and is one of the costliest chronic conditions.

Water quality prediction model using Gaussian process regression based on deep learning for carbon neutrality in papermaking wastewater treatment system.

Environmental research
Wastewater recycling is the measure with enormous potentiality to achieve carbon neutrality in wastewater treatment plants. High-precision online monitoring can improve the stability of wastewater treatment system and help wastewater recycling. A new...

From shallow to deep: some lessons learned from application of machine learning for recognition of functional genomic elements in human genome.

Human genomics
Identification of genomic signals as indicators for functional genomic elements is one of the areas that received early and widespread application of machine learning methods. With time, the methods applied grew in variety and generally exhibited a t...

Pattern Recognition of Holographic Image Library Based on Deep Learning.

Journal of healthcare engineering
The final loss function in the deep learning neural network is composed of other functions in the network. Due to the existence of a large number of non-linear functions such as activation functions in the network, the entire deep learning model pres...