AI Medical Compendium Topic:
Biomedical Research

Clear Filters Showing 521 to 530 of 546 articles

Opportunities and obstacles for deep learning in biology and medicine.

Journal of the Royal Society, Interface
Deep learning describes a class of machine learning algorithms that are capable of combining raw inputs into layers of intermediate features. These algorithms have recently shown impressive results across a variety of domains. Biology and medicine ar...

Biological Event Trigger Identification with Noise Contrastive Estimation.

IEEE/ACM transactions on computational biology and bioinformatics
Biological Event Extraction is an important task towards the goal of extracting biomedical knowledge from the scientific publications by capturing biomedical entities and their complex relations from the texts. As a crucial step in event extraction, ...

Automatic Processing of Anatomic Pathology Reports in the Italian Language to Enhance the Reuse of Clinical Data.

Studies in health technology and informatics
Medical reports often contain a lot of relevant information in the form of free text. To reuse these unstructured texts for biomedical research, it is important to extract structured data from them. In this work, we adapted a previously developed inf...

Revisit of Machine Learning Supported Biological and Biomedical Studies.

Methods in molecular biology (Clifton, N.J.)
Generally, machine learning includes many in silico methods to transform the principles underlying natural phenomenon to human understanding information, which aim to save human labor, to assist human judge, and to create human knowledge. It should h...

Identifying reports of randomized controlled trials (RCTs) via a hybrid machine learning and crowdsourcing approach.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVES: Identifying all published reports of randomized controlled trials (RCTs) is an important aim, but it requires extensive manual effort to separate RCTs from non-RCTs, even using current machine learning (ML) approaches. We aimed to make th...

["Handle with care": about the potential unintended consequences of oracular artificial intelligence systems in medicine.].

Recenti progressi in medicina
Decisional support systems based on machine learning (ML) in medicine are gaining a growing interest as some recent articles have highlighted the high diagnostic accuracy exhibited by these systems in specific medical contexts. However, it is implaus...

Finding useful data across multiple biomedical data repositories using DataMed.

Nature genetics
The value of broadening searches for data across multiple repositories has been identified by the biomedical research community. As part of the US National Institutes of Health (NIH) Big Data to Knowledge initiative, we work with an international com...