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Biomedical Research

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Evaluation of AIML + HDR-A Course to Enhance Data Science Workforce Capacity for Hispanic Biomedical Researchers.

International journal of environmental research and public health
Artificial intelligence (AI) and machine learning (ML) facilitate the creation of revolutionary medical techniques. Unfortunately, biases in current AI and ML approaches are perpetuating minority health inequity. One of the strategies to solve this p...

Generalized Generative Deep Learning Models for Biosignal Synthesis and Modality Transfer.

IEEE journal of biomedical and health informatics
Generative Adversarial Networks (GANs) are a revolutionary innovation in machine learning that enables the generation of artificial data. Artificial data synthesis is valuable especially in the medical field where it is difficult to collect and annot...

Ethics of Medical Archival Internet Research Data.

Journal of medical Internet research
Medical research based on internet archive data, which in some ways is quite different from other data-based studies, is becoming more and more common. Despite its uniqueness and the challenges that characterize it, clear ethical rules designed to gu...

Error-Correcting Mean-Teacher: Corrections instead of consistency-targets applied to semi-supervised medical image segmentation.

Computers in biology and medicine
Semantic segmentation is an essential task in medical imaging research. Many powerful deep-learning-based approaches can be employed for this problem, but they are dependent on the availability of an expansive labeled dataset. In this work, we augmen...

Artificial intelligence (AI) in biomedical research: discussion on authors' declaration of AI in their articles title.

European radiology experimental
Artificial intelligence (AI) and its different approaches, from machine learning to deep learning, are not new. We discuss here about the declaration of AI in the title of those articles dealing with AI. From 1990 to 2021, while AI articles in the Pu...

A Literature Review on Ethics for AI in Biomedical Research and Biobanking.

Yearbook of medical informatics
BACKGROUND: Artificial Intelligence (AI) is becoming more and more important especially in datacentric fields, such as biomedical research and biobanking. However, AI does not only offer advantages and promising benefits, but brings about also ethica...

Document-Level Chemical-Induced Disease Relation Extraction via Hierarchical Representation Learning.

IEEE/ACM transactions on computational biology and bioinformatics
Over the past decades, Chemical-induced Disease (CID) relations have attracted extensive attention in biomedical community, reflecting wide applications in biomedical research and healthcare field. However, prior efforts fail to make full use of the ...

Reducing systematic review burden using Deduklick: a novel, automated, reliable, and explainable deduplication algorithm to foster medical research.

Systematic reviews
BACKGROUND: Identifying and removing reference duplicates when conducting systematic reviews (SRs) remain a major, time-consuming issue for authors who manually check for duplicates using built-in features in citation managers. To address issues rela...

Understanding the Research Landscape of Deep Learning in Biomedical Science: Scientometric Analysis.

Journal of medical Internet research
BACKGROUND: Advances in biomedical research using deep learning techniques have generated a large volume of related literature. However, there is a lack of scientometric studies that provide a bird's-eye view of them. This absence has led to a partia...