[Retracted] U‐Net‐Based Medical Image Segmentation
Deep learning has been extensively applied to segmentation in medical imaging. U‐Net
proposed in 2015 shows the advantages of accurate segmentation of small targets and its …
proposed in 2015 shows the advantages of accurate segmentation of small targets and its …
Artificial intelligence in ophthalmology: The path to the real-world clinic
Artificial intelligence (AI) has great potential to transform healthcare by enhancing the
workflow and productivity of clinicians, enabling existing staff to serve more patients …
workflow and productivity of clinicians, enabling existing staff to serve more patients …
A survey on deep learning in medicine: Why, how and when?
New technologies are transforming medicine, and this revolution starts with data. Health
data, clinical images, genome sequences, data on prescribed therapies and results …
data, clinical images, genome sequences, data on prescribed therapies and results …
Artificial intelligence in colorectal cancer screening, diagnosis and treatment. A new era
The development of artificial intelligence (AI) algorithms has permeated the medical field
with great success. The widespread use of AI technology in diagnosing and treating several …
with great success. The widespread use of AI technology in diagnosing and treating several …
Reliable and resilient AI and IoT-based personalised healthcare services: A survey
Recent technological (eg, IoT, 5G), and economic (eg, UN 2030 Sustainable Development
Goals) developments have transformed the healthcare sector towards more personalized …
Goals) developments have transformed the healthcare sector towards more personalized …
Deep learning-based smart predictive evaluation for interactive multimedia-enabled smart healthcare
Two-dimensional arrays of bi-component structures made of cobalt and permalloy elliptical
dots with thickness of 25 nm, length 1 mm and width of 225 nm, have been prepared by a …
dots with thickness of 25 nm, length 1 mm and width of 225 nm, have been prepared by a …
A systematic review of natural language processing applied to radiology reports
Background Natural language processing (NLP) has a significant role in advancing
healthcare and has been found to be key in extracting structured information from radiology …
healthcare and has been found to be key in extracting structured information from radiology …
Deep representation learning of electronic health records to unlock patient stratification at scale
Deriving disease subtypes from electronic health records (EHRs) can guide next-generation
personalized medicine. However, challenges in summarizing and representing patient data …
personalized medicine. However, challenges in summarizing and representing patient data …
[HTML][HTML] Role of machine learning techniques to tackle the COVID-19 crisis: systematic review
Background: SARS-CoV-2, the novel coronavirus responsible for COVID-19, has caused
havoc worldwide, with patients presenting a spectrum of complications that have pushed …
havoc worldwide, with patients presenting a spectrum of complications that have pushed …
[HTML][HTML] Machine learning in clinical decision making
Machine learning is increasingly integrated into clinical practice, with applications ranging
from pre-clinical data processing, bedside diagnosis assistance, patient stratification …
from pre-clinical data processing, bedside diagnosis assistance, patient stratification …