An introductory review of deep learning for prediction models with big data
Deep learning models stand for a new learning paradigm in artificial intelligence (AI) and
machine learning. Recent breakthrough results in image analysis and speech recognition …
machine learning. Recent breakthrough results in image analysis and speech recognition …
Neural natural language processing for unstructured data in electronic health records: a review
Electronic health records (EHRs), digital collections of patient healthcare events and
observations, are ubiquitous in medicine and critical to healthcare delivery, operations, and …
observations, are ubiquitous in medicine and critical to healthcare delivery, operations, and …
Named entity recognition and relation detection for biomedical information extraction
The number of scientific publications in the literature is steadily growing, containing our
knowledge in the biomedical, health, and clinical sciences. Since there is currently no …
knowledge in the biomedical, health, and clinical sciences. Since there is currently no …
Artificial intelligence-driven biomedical genomics
As genomic research becomes more complex and data-rich, artificial intelligence (AI) has
emerged as a crucial tool for processing and analyzing high-dimensional genomic data …
emerged as a crucial tool for processing and analyzing high-dimensional genomic data …
[HTML][HTML] Clinical characteristics and prognostic factors for intensive care unit admission of patients with COVID-19: retrospective study using machine learning and …
JL Izquierdo, J Ancochea… - Journal of medical …, 2020 - jmir.org
Background Many factors involved in the onset and clinical course of the ongoing COVID-19
pandemic are still unknown. Although big data analytics and artificial intelligence are widely …
pandemic are still unknown. Although big data analytics and artificial intelligence are widely …
Artificial intelligence in rheumatoid arthritis: current status and future perspectives: a state-of-the-art review
Investigation of the potential applications of artificial intelligence (AI), including machine
learning (ML) and deep learning (DL) techniques, is an exponentially growing field in …
learning (ML) and deep learning (DL) techniques, is an exponentially growing field in …
Natural language processing with machine learning methods to analyze unstructured patient-reported outcomes derived from electronic health records: A systematic …
Objective Natural language processing (NLP) combined with machine learning (ML)
techniques are increasingly used to process unstructured/free-text patient-reported outcome …
techniques are increasingly used to process unstructured/free-text patient-reported outcome …
Basic of machine learning and deep learning in imaging for medical physicists
L Manco, N Maffei, S Strolin, S Vichi, L Bottazzi… - Physica Medica, 2021 - Elsevier
The manuscript aims at providing an overview of the published algorithms/automation tool
for artificial intelligence applied to imaging for Healthcare. A PubMed search was performed …
for artificial intelligence applied to imaging for Healthcare. A PubMed search was performed …
Medical text classification using hybrid deep learning models with multihead attention
SK Prabhakar, DO Won - Computational intelligence and …, 2021 - Wiley Online Library
To unlock information present in clinical description, automatic medical text classification is
highly useful in the arena of natural language processing (NLP). For medical text …
highly useful in the arena of natural language processing (NLP). For medical text …
How data science and AI-based technologies impact genomics
J Lin, KY Ngiam - Singapore medical journal, 2023 - journals.lww.com
Advancements in high-throughput sequencing have yielded vast amounts of genomic data,
which are studied using genome-wide association study (GWAS)/phenome-wide …
which are studied using genome-wide association study (GWAS)/phenome-wide …