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Biomedical Research

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A deep-learning system bridging molecule structure and biomedical text with comprehension comparable to human professionals.

Nature communications
To accelerate biomedical research process, deep-learning systems are developed to automatically acquire knowledge about molecule entities by reading large-scale biomedical data. Inspired by humans that learn deep molecule knowledge from versatile rea...

The BMS-LM ontology for biomedical data reporting throughout the lifecycle of a research study: From data model to ontology.

Journal of biomedical informatics
Biomedical research data reuse and sharing is essential for fostering research progress. To this aim, data producers need to master data management and reporting through standard and rich metadata, as encouraged by open data initiatives such as the F...

Nurturing diversity and inclusion in AI in Biomedicine through a virtual summer program for high school students.

PLoS computational biology
Artificial Intelligence (AI) has the power to improve our lives through a wide variety of applications, many of which fall into the healthcare space; however, a lack of diversity is contributing to limitations in how broadly AI can help people. The U...

Fulfilling the Promise of Artificial Intelligence in the Health Sector: Let's Get Real.

Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research
OBJECTIVES: This study aimed to showcase the potential and key concerns and risks of artificial intelligence (AI) in the health sector, illustrating its application with current examples, and to provide policy guidance for the development, assessment...

Translatability Analysis of National Institutes of Health-Funded Biomedical Research That Applies Artificial Intelligence.

JAMA network open
IMPORTANCE: Despite the rapid growth of interest and diversity in applications of artificial intelligence (AI) to biomedical research, there are limited objective ways to characterize the potential for use of AI in clinical practice.

AMMU: A survey of transformer-based biomedical pretrained language models.

Journal of biomedical informatics
Transformer-based pretrained language models (PLMs) have started a new era in modern natural language processing (NLP). These models combine the power of transformers, transfer learning, and self-supervised learning (SSL). Following the success of th...

Ghost in the machine or monkey with a typewriter-generating titles for Christmas research articles in using artificial intelligence: observational study.

BMJ (Clinical research ed.)
OBJECTIVE: To determine whether artificial intelligence (AI) can generate plausible and engaging titles for potential Christmas research articles in .

Biomarker discovery studies for patient stratification using machine learning analysis of omics data: a scoping review.

BMJ open
OBJECTIVE: To review biomarker discovery studies using omics data for patient stratification which led to clinically validated FDA-cleared tests or laboratory developed tests, in order to identify common characteristics and derive recommendations for...

Detecting fabrication in large-scale molecular omics data.

PloS one
Fraud is a pervasive problem and can occur as fabrication, falsification, plagiarism, or theft. The scientific community is not exempt from this universal problem and several studies have recently been caught manipulating or fabricating data. Current...

Research Progress of Gliomas in Machine Learning.

Cells
In the field of gliomas research, the broad availability of genetic and image information originated by computer technologies and the booming of biomedical publications has led to the advent of the big-data era. Machine learning methods were applied ...