Artificial intelligence in cardiology: present and future

F Lopez-Jimenez, Z Attia, AM Arruda-Olson… - Mayo Clinic …, 2020 - Elsevier
Artificial intelligence (AI) is a nontechnical, popular term that refers to machine learning of
various types but most often to deep neural networks. Cardiology is at the forefront of AI in …

[HTML][HTML] The role of telemedicine in postoperative care

AM Williams, UF Bhatti, HB Alam, VC Nikolian - Mhealth, 2018 - ncbi.nlm.nih.gov
Telemedicine has become one of the most rapidly-expanding components of the health care
system. Its adoption has afforded improved access to care, greater resource efficiency, and …

Artificial intelligence–enabled electrocardiograms for identification of patients with low ejection fraction: a pragmatic, randomized clinical trial

X Yao, DR Rushlow, JW Inselman, RG McCoy… - Nature Medicine, 2021 - nature.com
We have conducted a pragmatic clinical trial aimed to assess whether an electrocardiogram
(ECG)-based, artificial intelligence (AI)-powered clinical decision support tool enables early …

Multi-expert performance evaluation of healthcare institutions using an integrated intuitionistic fuzzy AHP&DEA methodology

İ Otay, B Oztaysi, SC Onar, C Kahraman - Knowledge-Based Systems, 2017 - Elsevier
Healthcare management and healthcare industry have been one of the popular and
complex topics that many researchers and professionals have focused on. This paper …

Transforming epilepsy research: A systematic review on natural language processing applications

ANJ Yew, M Schraagen, WM Otte, E van Diessen - Epilepsia, 2023 - Wiley Online Library
Despite improved ancillary investigations in epilepsy care, patients' narratives remain
indispensable for diagnosing and treatment monitoring. This wealth of information is …

Desiderata for delivering NLP to accelerate healthcare AI advancement and a Mayo Clinic NLP-as-a-service implementation

A Wen, S Fu, S Moon, M El Wazir, A Rosenbaum… - NPJ digital …, 2019 - nature.com
Data is foundational to high-quality artificial intelligence (AI). Given that a substantial amount
of clinically relevant information is embedded in unstructured data, natural language …

Big data analytics enhanced healthcare systems: a review

S Shafqat, S Kishwer, RU Rasool, J Qadir… - The Journal of …, 2020 - Springer
There is increased interest in deploying big data technology in the healthcare industry to
manage massive collections of heterogeneous health datasets such as electronic health …

Using electronic health records to generate phenotypes for research

SA Pendergrass, DC Crawford - Current protocols in human …, 2019 - Wiley Online Library
Electronic health records contain patient‐level data collected during and for clinical care.
Data within the electronic health record include diagnostic billing codes, procedure codes …

[HTML][HTML] Big data handling mechanisms in the healthcare applications: A comprehensive and systematic literature review

A Pashazadeh, NJ Navimipour - Journal of biomedical informatics, 2018 - Elsevier
Healthcare provides many services such as diagnosing, treatment, prevention of diseases,
illnesses, injuries, and other physical and mental disorders. Large-scale distributed data …

OCR as a service: an experimental evaluation of Google Docs OCR, Tesseract, ABBYY FineReader, and Transym

AP Tafti, A Baghaie, M Assefi, HR Arabnia, Z Yu… - Advances in Visual …, 2016 - Springer
Optical character recognition (OCR) as a classic machine learning challenge has been a
longstanding topic in a variety of applications in healthcare, education, insurance, and legal …