Results 21 to 30 of about 26,844,009 (300)

A Comprehensive Survey on Machine Learning-Based Big Data Analytics for IoT-Enabled Smart Healthcare System

Journal on spesial topics in mobile networks and applications, 2021
The outbreak of chronic diseases such as COVID-19 has made a renewed call for providing urgent healthcare facilities to the citizens across the globe.
Wei Li, Yuanbo Chai, Fazlullah Khan, Syed Roohullah Jan, Sahil Verma, Varun G. Menon, Kavita, Xingwang Li   +7 more
semanticscholar   +1 more source

Factors Influencing the Adoption of Big Data Analytics in the Digital Transformation Era: Case Study of Jordanian SMEs

Sustainability, 2022
Big data (BD) analytics has been increasingly gaining attraction in both practice and theory in light of its opportunities, barriers and expected benefits.
Abdalwali Lutfi, Adi Alsyouf, Mohammed Amin Almaiah, Mahmoud Alrawad, Ahmed Abdullah Khalil Abdo, Akif Al-Khasawneh, Nahla Ibrahim, M. Saad   +7 more
semanticscholar   +1 more source

Towards precision medicine: discovering novel gynecological cancer biomarkers and pathways using linked data

Journal of Biomedical Semantics, 2017
Background Next Generation Sequencing (NGS) is playing a key role in therapeutic decision making for the cancer prognosis and treatment. The NGS technologies are producing a massive amount of sequencing datasets.
Alokkumar Jha, Yasar Khan, Muntazir Mehdi, Md Rezaul Karim, Qaiser Mehmood, Achille Zappa, Dietrich Rebholz-Schuhmann, Ratnesh Sahay   +7 more
doaj   +1 more source

Innovations in Genomics and Big Data Analytics for Personalized Medicine and Health Care: A Review

International Journal of Molecular Sciences, 2022
Big data in health care is a fast-growing field and a new paradigm that is transforming case-based studies to large-scale, data-driven research. As big data is dependent on the advancement of new data standards, technology, and relevant research, the ...
Mubashir Hassan, F. Awan, Anam Naz, Enrique J. deAndrés-Galiana, Óscar Álvarez, A. Cernea, Lucas Fernández-Brillet, J. Fernández-Martínez, A. Kloczkowski   +8 more
semanticscholar   +1 more source

Enhancing Digital Health Services with Big Data Analytics

Big Data and Cognitive Computing, 2023
Medicine is constantly generating new imaging data, including data from basic research, clinical research, and epidemiology, from health administration and insurance organizations, public health services, and non-conventional data sources such as social ...
Nisrine Berros, Fatna El Mendili, Youness Filaly, Y. Idrissi   +3 more
semanticscholar   +1 more source

Strengthening and expanding health inequality monitoring for the advancement of health equity: a review of WHO resources and contributions

International Journal for Equity in Health, 2023
As part of its commitment to advance health equity, the World Health Organization (WHO) has a developed area of work to promote and strengthen health inequality monitoring.
Ahmad Reza Hosseinpoor, Nicole Bergen, Katherine Kirkby, Anne Schlotheuber   +3 more
doaj   +1 more source

DeepTRIAGE: interpretable and individualised biomarker scores using attention mechanism for the classification of breast cancer sub-types

BMC Medical Genomics, 2020
Background Breast cancer is a collection of multiple tissue pathologies, each with a distinct molecular signature that correlates with patient prognosis and response to therapy.
Adham Beykikhoshk, Thomas P. Quinn, Samuel C. Lee, Truyen Tran, Svetha Venkatesh   +4 more
doaj   +1 more source

DARES: An Asynchronous Distributed Recommender System Using Deep Reinforcement Learning

IEEE Access, 2021
Traditional Recommender Systems (RS) use central servers to collect user data, compute user profiles and train global recommendation models. Central computation of RS models has great results in performance because the models are trained using all the ...
Bichen Shi, Elias Z. Tragos, Makbule Gulcin Ozsoy, Ruihai Dong, Neil Hurley, Barry Smyth, Aonghus Lawlor   +6 more
doaj   +1 more source

scConsensus: combining supervised and unsupervised clustering for cell type identification in single-cell RNA sequencing data

BMC Bioinformatics, 2021
Background Clustering is a crucial step in the analysis of single-cell data. Clusters identified in an unsupervised manner are typically annotated to cell types based on differentially expressed genes.
Bobby Ranjan, Florian Schmidt, Wenjie Sun, Jinyu Park, Mohammad Amin Honardoost, Joanna Tan, Nirmala Arul Rayan, Shyam Prabhakar   +7 more
doaj   +1 more source

Data Analytics in Action

, 2023
The previous chapters provided gentle introductions to various important topics in the area of data analytics. In this chapter, we present three real-life case studies that illustrate how the methods and approaches outlined in the previous chapters can be put into practice.
Schouten, Gerard, Arena, Giuseppe, Leeuwen, Frederique van, Heck, Petra, Mulder, Joris, Aalbers, Rick, Leenders, Roger, Böing-Messing, Florian   +7 more
openaire   +2 more sources