AIMC Topic: Big Data

Clear Filters Showing 491 to 500 of 659 articles

Predicting Protein Function in the AI and Big Data Era.

Biochemistry
It is an exciting time for researchers working to link proteins to their functions. Most techniques for extracting functional information from genomic sequences were developed several years ago, with major progress driven by the availability of big d...

Developmental toxicity: artificial intelligence-powered assessments.

Trends in pharmacological sciences
Regulatory agencies require comprehensive toxicity testing for prenatal drug exposure, including new drugs in development, to reduce concerns about developmental toxicity, that is, drug-induced toxicity and adverse effects in pregnant women and fetus...

Accelerating autism spectrum disorder care: A rapid review of data science applications in diagnosis and intervention.

Asian journal of psychiatry
Integrating data science techniques, including machine learning, natural language processing, and big data analytics, has revolutionized the diagnosis and intervention landscape for Autism Spectrum Disorder (ASD). This rapid review examines these app...

Barriers and Facilitators for Federated Health Data Networks: Lessons Learned from a Nordic-Baltic Experience.

Studies in health technology and informatics
The era of artificial intelligence (AI) and big data presents significant opportunities for implementing federated health data networks across national borders. However, these opportunities are accompanied by substantial challenges. This study docume...

Context-Contingent Privacy Concerns and Exploration of the Privacy Paradox in the Age of AI, Augmented Reality, Big Data, and the Internet of Things: Systematic Review.

Journal of medical Internet research
BACKGROUND: Despite extensive research into technology users' privacy concerns, a critical gap remains in understanding why individuals adopt different standards for data protection across contexts. The rise of advanced technologies such as the Inter...

Enrichment Analysis and Deep Learning in Biomedical Ontology: Applications and Advancements.

Chinese medical sciences journal = Chung-kuo i hsueh k'o hsueh tsa chih
Biomedical big data, characterized by its massive scale, multi-dimensionality, and heterogeneity, offers novel perspectives for disease research, elucidates biological principles, and simultaneously prompts changes in related research methodologies. ...

Big data analytics and machine learning in hematology: Transformative insights, applications and challenges.

Medicine
The integration of big data analytics and machine learning (ML) into hematology has ushered in a new era of precision medicine, offering transformative insights into disease management. By leveraging vast and diverse datasets, including genomic profi...

Ethical considerations on the use of big data and artificial intelligence in kidney research from the ERA ethics committee.

Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association
In the current paper, we will focus on requirements to ensure big data can advance the outcomes of our patients suffering from kidney disease. The associated ethical question is whether and how we as a nephrology community can and should encourage th...

Beyond the hype: using AI, big data, wearable devices, and the internet of things for high-throughput livestock phenotyping.

Briefings in functional genomics
Phenotyping of animals is a routine task in agriculture which can provide large datasets for the functional annotation of genomes. Using the livestock farming sector to study complex traits enables genetics researchers to fully benefit from the digit...

Leveraging big data in health care and public health for AI driven talent development in rural areas.

Frontiers in public health
INTRODUCTION: This study proposes a novel Transformer-based approach to enhance talent attraction and retention strategies in rural public health systems. Motivated by the persistent shortage of skilled professionals in underserved areas and the limi...