AIMC Topic: Reproducibility of Results

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Machine learning based brain tumour segmentation on limited data using local texture and abnormality.

Computers in biology and medicine
Brain tumour segmentation in medical images is a very challenging task due to the large variety in tumour shape, position, appearance, scanning modalities and scanning parameters. Most existing segmentation algorithms use information from four differ...

Identifying β-thalassemia carriers using a data mining approach: The case of the Gaza Strip, Palestine.

Artificial intelligence in medicine
Thalassemia is considered one of the most common genetic blood disorders that has received excessive attention in the medical research fields worldwide. Under this context, one of the greatest challenges for healthcare professionals is to correctly d...

Lung sounds classification using convolutional neural networks.

Artificial intelligence in medicine
Lung sounds convey relevant information related to pulmonary disorders, and to evaluate patients with pulmonary conditions, the physician or the doctor uses the traditional auscultation technique. However, this technique suffers from limitations. For...

Machine learning in cardiac CT: Basic concepts and contemporary data.

Journal of cardiovascular computed tomography
Propelled by the synergy of the groundbreaking advancements in the ability to analyze high-dimensional datasets and the increasing availability of imaging and clinical data, machine learning (ML) is poised to transform the practice of cardiovascular ...

Small lung nodules detection based on local variance analysis and probabilistic neural network.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: In medical examinations doctors use various techniques in order to provide to the patients an accurate analysis of their actual state of health. One of the commonly used methodologies is the x-ray screening. This examination...

Transferring and generalizing deep-learning-based neural encoding models across subjects.

NeuroImage
Recent studies have shown the value of using deep learning models for mapping and characterizing how the brain represents and organizes information for natural vision. However, modeling the relationship between deep learning models and the brain (or ...

Label-indicator morpheme growth on LSTM for Chinese healthcare question department classification.

Journal of biomedical informatics
BACKGROUND: Current Chinese medicine has an urgent demand for convenient medical services. When facing a large number of patients, understanding patients' questions automatically and precisely is useful. Different from the high professional medical t...

Drug Repositioning by Integrating Known Disease-Gene and Drug-Target Associations in a Semi-supervised Learning Model.

Acta biotheoretica
Computational drug repositioning has been proven as a promising and efficient strategy for discovering new uses from existing drugs. To achieve this goal, a number of computational methods have been proposed, which are based on different data sources...

Natural Language Processing Accurately Calculates Adenoma and Sessile Serrated Polyp Detection Rates.

Digestive diseases and sciences
BACKGROUND: ADR is a widely used colonoscopy quality indicator. Calculation of ADR is labor-intensive and cumbersome using current electronic medical databases. Natural language processing (NLP) is a method used to extract meaning from unstructured o...