AIMC Topic: Big Data

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Data infrastructures for AI in medical imaging: a report on the experiences of five EU projects.

European radiology experimental
Artificial intelligence (AI) is transforming the field of medical imaging and has the potential to bring medicine from the era of 'sick-care' to the era of healthcare and prevention. The development of AI requires access to large, complete, and harmo...

Classification of skin cancer stages using a AHP fuzzy technique within the context of big data healthcare.

Journal of cancer research and clinical oncology
BACKGROUND AND OBJECTIVES: Skin conditions in humans can be challenging to diagnose. Skin cancer manifests itself without warning. In the future, these illnesses, which have been an issue for many, will be identified and treated. With the rapid expan...

Digital Transformation of Cancer Care in the Era of Big Data, Artificial Intelligence and Data-Driven Interventions: Navigating the Field.

Seminars in oncology nursing
OBJECTIVES: To navigate the field of digital cancer care and define and discuss key aspects and applications of big data analytics, artificial intelligence (AI), and data-driven interventions.

PathologyBERT - Pre-trained Vs. A New Transformer Language Model for Pathology Domain.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Pathology text mining is a challenging task given the reporting variability and constant new findings in cancer sub-type definitions. However, successful text mining of a large pathology database can play a critical role to advance 'big data' cancer ...

Small Data Can Play a Big Role in Chemical Discovery.

Angewandte Chemie (International ed. in English)
The chemistry community is currently witnessing a surge of scientific discoveries in organic chemistry supported by machine learning (ML) techniques. Whereas many of these techniques were developed for big data applications, the nature of experimenta...

From Big Data's 5Vs to clinical practice's 5Ws: enhancing data-driven decision making in healthcare.

Journal of clinical monitoring and computing
The use of AI-based algorithms is rapidly growing in healthcare, but there is still an ongoing debate about how to manage and ensure accountability for their clinical use. While most of the studies focus on demonstrating a good algorithm performance ...

From Deep Mutational Mapping of Allosteric Protein Landscapes to Deep Learning of Allostery and Hidden Allosteric Sites: Zooming in on "Allosteric Intersection" of Biochemical and Big Data Approaches.

International journal of molecular sciences
The recent advances in artificial intelligence (AI) and machine learning have driven the design of new expert systems and automated workflows that are able to model complex chemical and biological phenomena. In recent years, machine learning approach...

Big Data, Machine Learning, and Artificial Intelligence to Advance Cancer Care: Opportunities and Challenges.

Seminars in oncology nursing
OBJECTIVES: The rapid advances in artificial intelligence (AI), big data, and machine learning (ML) technologies hold promise for personalized, equitable cancer care and improved health outcomes within the context of cancer and beyond. Furthermore, i...

Modified CPT-TODIM method for evaluating the development level of digital inclusive finance under probabilistic hesitant fuzzy environment.

PloS one
Unlike traditional finance, digital inclusive finance is committed to integrating digital technology with the financial industry to bring groups originally excluded from traditional finance back into formal financial services and provide financial se...