Desiderata for delivering NLP to accelerate healthcare AI advancement and a Mayo Clinic NLP-as-a-service implementation
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 …
of clinically relevant information is embedded in unstructured data, natural language …
Applications of machine learning to undifferentiated chest pain in the emergency department: A systematic review
J Stewart, J Lu, A Goudie, M Bennamoun, P Sprivulis… - PloS one, 2021 - journals.plos.org
Background Chest pain is amongst the most common reason for presentation to the
emergency department (ED). There are many causes of chest pain, and it is important for the …
emergency department (ED). There are many causes of chest pain, and it is important for the …
Machine learning for ECG diagnosis and risk stratification of occlusion myocardial infarction
Patients with occlusion myocardial infarction (OMI) and no ST-elevation on presenting
electrocardiogram (ECG) are increasing in numbers. These patients have a poor prognosis …
electrocardiogram (ECG) are increasing in numbers. These patients have a poor prognosis …
Machine learning-based prediction of acute coronary syndrome using only the pre-hospital 12-lead electrocardiogram
Prompt identification of acute coronary syndrome is a challenge in clinical practice. The 12-
lead electrocardiogram (ECG) is readily available during initial patient evaluation, but …
lead electrocardiogram (ECG) is readily available during initial patient evaluation, but …
Machine learning for subtype definition and risk prediction in heart failure, acute coronary syndromes and atrial fibrillation: systematic review of validity and clinical …
Background Machine learning (ML) is increasingly used in research for subtype definition
and risk prediction, particularly in cardiovascular diseases. No existing ML models are …
and risk prediction, particularly in cardiovascular diseases. No existing ML models are …
Artificial intelligence in cardiovascular medicine: current insights and future prospects
Cardiovascular disease (CVD) represents a significant and increasing burden on healthcare
systems. Artificial intelligence (AI) is a rapidly evolving transdisciplinary field employing …
systems. Artificial intelligence (AI) is a rapidly evolving transdisciplinary field employing …
[HTML][HTML] Application of machine learning approaches for osteoporosis risk prediction in postmenopausal women
Many predictive tools have been reported for assessing osteoporosis risk. The development
and validation of osteoporosis risk prediction models were supported by machine learning …
and validation of osteoporosis risk prediction models were supported by machine learning …
Review of artificial intelligence application in cardiology
A Šećkanović, M Šehovac, L Spahić… - 2020 9th …, 2020 - ieeexplore.ieee.org
Increasing incidence of cardiovascular disease and their mortality rate render them as
second leading cause of death worldwide. Artificial Intelligence (AI) is used in many fields of …
second leading cause of death worldwide. Artificial Intelligence (AI) is used in many fields of …
Artificial intelligence-assisted remote detection of ST-elevation myocardial infarction using a mini-12-lead electrocardiogram device in prehospital ambulance care
KW Chen, YC Wang, MH Liu, BY Tsai… - Frontiers in …, 2022 - frontiersin.org
Objective To implement an all-day online artificial intelligence (AI)-assisted detection of ST-
elevation myocardial infarction (STEMI) by prehospital 12-lead electrocardiograms (ECGs) …
elevation myocardial infarction (STEMI) by prehospital 12-lead electrocardiograms (ECGs) …
Survey and evaluation of hypertension machine learning research
Background Machine learning (ML) is pervasive in all fields of research, from automating
tasks to complex decision‐making. However, applications in different specialities are …
tasks to complex decision‐making. However, applications in different specialities are …