Fusion of medical imaging and electronic health records using deep learning: a systematic review and implementation guidelines
Advancements in deep learning techniques carry the potential to make significant
contributions to healthcare, particularly in fields that utilize medical imaging for diagnosis …
contributions to healthcare, particularly in fields that utilize medical imaging for diagnosis …
A Technical Review of Convolutional Neural Network‐Based Mammographic Breast Cancer Diagnosis
This study reviews the technique of convolutional neural network (CNN) applied in a specific
field of mammographic breast cancer diagnosis (MBCD). It aims to provide several clues on …
field of mammographic breast cancer diagnosis (MBCD). It aims to provide several clues on …
Integrated multimodal artificial intelligence framework for healthcare applications
Artificial intelligence (AI) systems hold great promise to improve healthcare over the next
decades. Specifically, AI systems leveraging multiple data sources and input modalities are …
decades. Specifically, AI systems leveraging multiple data sources and input modalities are …
Multimodal fusion with deep neural networks for leveraging CT imaging and electronic health record: a case-study in pulmonary embolism detection
Recent advancements in deep learning have led to a resurgence of medical imaging and
Electronic Medical Record (EMR) models for a variety of applications, including clinical …
Electronic Medical Record (EMR) models for a variety of applications, including clinical …
[HTML][HTML] Review of multimodal machine learning approaches in healthcare
Abstract Machine learning methods in healthcare have traditionally focused on using data
from a single modality, limiting their ability to effectively replicate the clinical practice of …
from a single modality, limiting their ability to effectively replicate the clinical practice of …
Artificial neural network based breast cancer screening: a comprehensive review
Breast cancer is a common fatal disease for women. Early diagnosis and detection is
necessary in order to improve the prognosis of breast cancer affected people. For predicting …
necessary in order to improve the prognosis of breast cancer affected people. For predicting …
Glaucoma management in the era of artificial intelligence
Glaucoma is a result of irreversible damage to the retinal ganglion cells. While an early
intervention could minimise the risk of vision loss in glaucoma, its asymptomatic nature …
intervention could minimise the risk of vision loss in glaucoma, its asymptomatic nature …
Comprehensive review on the use of artificial intelligence in ophthalmology and future research directions
Background: Having several applications in medicine, and in ophthalmology in particular,
artificial intelligence (AI) tools have been used to detect visual function deficits, thus playing …
artificial intelligence (AI) tools have been used to detect visual function deficits, thus playing …
Artificial intelligence in glaucoma
C Zheng, TV Johnson, A Garg… - Current opinion in …, 2019 - journals.lww.com
Artificial intelligence has the potential to revolutionize the screening, diagnosis, and
classification of glaucoma, both through the automated processing of large data sets, and by …
classification of glaucoma, both through the automated processing of large data sets, and by …
Artificial intelligence (AI) impacting diagnosis of glaucoma and understanding the regulatory aspects of AI-based software as medical device
B Prabhakar, RK Singh, KS Yadav - Computerized Medical Imaging and …, 2021 - Elsevier
Glaucoma, the group of eye diseases is characterized by increased intraocular pressure,
optic neuropathy and visual field defect patterns. Early and correct diagnosis of glaucoma …
optic neuropathy and visual field defect patterns. Early and correct diagnosis of glaucoma …