AIMC Topic: Databases, Factual

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DePicT Melanoma Deep-CLASS: a deep convolutional neural networks approach to classify skin lesion images.

BMC bioinformatics
BACKGROUND: Melanoma results in the vast majority of skin cancer deaths during the last decades, even though this disease accounts for only one percent of all skin cancers' instances. The survival rates of melanoma from early to terminal stages is mo...

CAPTCHA Image Generation: Two-Step Style-Transfer Learning in Deep Neural Networks.

Sensors (Basel, Switzerland)
Mobile devices such as sensors are used to connect to the Internet and provide services to users. Web services are vulnerable to automated attacks, which can restrict mobile devices from accessing websites. To prevent such automated attacks, CAPTCHAs...

Addressing database variability in learning from medical data: An ensemble-based approach using convolutional neural networks and a case of study applied to automatic sleep scoring.

Computers in biology and medicine
In this work we examine some of the problems associated with the development of machine learning models with the objective to achieve robust generalization capabilities on common-task multiple-database scenarios. Referred to as the "database variabil...

Breaking Down Structural Diversity for Comprehensive Prediction of Ion-Neutral Collision Cross Sections.

Analytical chemistry
Identification of unknowns is a bottleneck for large-scale untargeted analyses like metabolomics or drug metabolite identification. Ion mobility-mass spectrometry (IM-MS) provides rapid two-dimensional separation of ions based on their mobility throu...

NFN+: A novel network followed network for retinal vessel segmentation.

Neural networks : the official journal of the International Neural Network Society
In the early diagnosis of diabetic retinopathy, the morphological attributes of blood vessels play an essential role to construct a retinal computer-aided diagnosis system. However, due to the challenges including limited densely annotated data, inte...

Machine Learning Based Opioid Overdose Prediction Using Electronic Health Records.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Opioid addiction in the United States has come to national attention as opioid overdose (OD) related deaths have risen at alarming rates. Combating opioid epidemic becomes a high priority for not only governments but also healthcare providers. This d...

Predicting Adverse Drug Reactions on Distributed Health Data using Federated Learning.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Using electronic health data to predict adverse drug reaction (ADR) incurs practical challenges, such as lack of adequate data from any single site for rare ADR detection, resource constraints on integrating data from multiple sources, and privacy co...

A Residual Based Attention Model for EEG Based Sleep Staging.

IEEE journal of biomedical and health informatics
Sleep staging is to score the sleep state of a subject into different sleep stages such as Wake and Rapid Eye Movement (REM). It plays an indispensable role in the diagnosis and treatment of sleep disorders. As manual sleep staging through well-train...