AIMC Topic: Reproducibility of Results

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Localization of common carotid artery transverse section in B-mode ultrasound images using faster RCNN: a deep learning approach.

Medical & biological engineering & computing
Cardiologists can acquire important information related to patients' cardiac health using carotid artery stiffness, its lumen diameter (LD), and its carotid intima-media thickness (cIMT). The sonographers primarily concern about the location of the a...

Real-Time Detection of Compensatory Patterns in Patients With Stroke to Reduce Compensation During Robotic Rehabilitation Therapy.

IEEE journal of biomedical and health informatics
OBJECTIVES: Compensations are commonly employed by patients with stroke during rehabilitation without therapist supervision, leading to suboptimal recovery outcomes. This study investigated the feasibility of the real-time monitoring of compensation ...

International evaluation of an AI system for breast cancer screening.

Nature
Screening mammography aims to identify breast cancer at earlier stages of the disease, when treatment can be more successful. Despite the existence of screening programmes worldwide, the interpretation of mammograms is affected by high rates of false...

A new backpropagation neural network classification model for prediction of incidence of malaria.

Frontiers in bioscience (Landmark edition)
Malaria is an infectious disease caused by parasitic protozoans of the Plasmodium family. These parasites are transmitted by mosquitos which are common in certain parts of the world. Based on their specific climates, these regions have been classifie...

Seeking for potential pathogenic genes of major depressive disorder in the Gene Expression Omnibus database.

Asia-Pacific psychiatry : official journal of the Pacific Rim College of Psychiatrists
INTRODUCTION: Major depressive disorder (MDD) is one of the most common mental disorders worldwide. The aim of this study was to identify potential pathological genes in MDD.

Using transfer learning from prior reference knowledge to improve the clustering of single-cell RNA-Seq data.

Scientific reports
In many research areas scientists are interested in clustering objects within small datasets while making use of prior knowledge from large reference datasets. We propose a method to apply the machine learning concept of transfer learning to unsuperv...

Prediction of IDH and TERT promoter mutations in low-grade glioma from magnetic resonance images using a convolutional neural network.

Scientific reports
Identification of genotypes is crucial for treatment of glioma. Here, we developed a method to predict tumor genotypes using a pretrained convolutional neural network (CNN) from magnetic resonance (MR) images and compared the accuracy to that of a di...

Rule-based and machine learning algorithms identify patients with systemic sclerosis accurately in the electronic health record.

Arthritis research & therapy
BACKGROUND: Systemic sclerosis (SSc) is a rare disease with studies limited by small sample sizes. Electronic health records (EHRs) represent a powerful tool to study patients with rare diseases such as SSc, but validated methods are needed. We devel...