| no |
title |
author |
magazine |
year |
volume |
issue |
page(s) |
type |
| 1 |
A cortical thinning signature to identify World Trade Center responders with possible dementia
|
Clouston, Sean A.P.
|
|
|
5 |
C |
p.
|
article
|
| 2 |
A critical analysis of COVID-19 research literature: Text mining approach
|
Zengul, Ferhat D.
|
|
|
5 |
C |
p.
|
article
|
| 3 |
A Machine Learning Algorithm Predicts Duration of hospitalization in COVID-19 patients
|
Ebinger, Joseph
|
|
|
5 |
C |
p.
|
article
|
| 4 |
An ensemble approach for multi-stage transfer learning models for COVID-19 detection from chest CT scans
|
Hernández Santa Cruz, Jose Francisco
|
|
|
5 |
C |
p.
|
article
|
| 5 |
A novel data augmentation approach for mask detection using deep transfer learning
|
Prusty, Manas Ranjan
|
|
|
5 |
C |
p.
|
article
|
| 6 |
Appropriate use of machine learning in healthcare
|
Ozaydin, Bunyamin
|
|
|
5 |
C |
p.
|
article
|
| 7 |
Artificial intelligence for diagnosis of fractures on plain radiographs: A scoping review of current literature
|
Rainey, Clare
|
|
|
5 |
C |
p.
|
article
|
| 8 |
A super learner ensemble of 14 statistical learning models for predicting COVID-19 severity among patients with cardiovascular conditions
|
Ehwerhemuepha, Louis
|
|
|
5 |
C |
p.
|
article
|
| 9 |
Auto-contouring FDG-PET/MR images for cervical cancer radiation therapy: An intelligent sequential approach using focally trained, shallow U-Nets
|
Baydoun, Atallah
|
|
|
5 |
C |
p.
|
article
|
| 10 |
Automated analysis of ambulatory surgery patient experience comments using artificial intelligence for quality improvement: A patient centered approach
|
Mathur, Piyush
|
|
|
5 |
C |
p.
|
article
|
| 11 |
Automated diabetic retinopathy screening for primary care settings using deep learning
|
Bhuiyan, Alauddin
|
|
|
5 |
C |
p.
|
article
|
| 12 |
Classification of Cervical Intraepithelial Neoplasia (CIN) using fine-tuned Convolutional Neural Networks
|
Aina, Oluwatomisin E.
|
|
|
5 |
C |
p.
|
article
|
| 13 |
Glaucoma detection in retinal fundus images using U-Net and supervised machine learning algorithms
|
Shinde, Rutuja
|
|
|
5 |
C |
p.
|
article
|
| 14 |
HeartPredict algorithm: Machine intelligence for the early detection of heart failure
|
Amadou Boubacar, Habiboulaye
|
|
|
5 |
C |
p.
|
article
|
| 15 |
Integration of a deep learning system for automated chest x-ray interpretation in the emergency department: A proof-of-concept
|
Mosquera, Candelaria
|
|
|
5 |
C |
p.
|
article
|
| 16 |
Medical image editing in the latent space of Generative Adversarial Networks
|
Fernández Blanco, Rubén
|
|
|
5 |
C |
p.
|
article
|
| 17 |
Optimal hyperparameter selection of deep learning models for COVID-19 chest X-ray classification
|
Adedigba, Adeyinka P.
|
|
|
5 |
C |
p.
|
article
|
| 18 |
Physician documentation matters. Using natural language processing to predict mortality in sepsis
|
Cooley-Rieders, Keaton
|
|
|
5 |
C |
p.
|
article
|
| 19 |
Predicting shunt infection in children with hydrocephalus
|
Sabeti, M.
|
|
|
5 |
C |
p.
|
article
|
| 20 |
Publishing Artificial Intelligence research papers: A tale of three journals
|
Shortliffe, Edward H.
|
|
|
5 |
C |
p.
|
article
|
| 21 |
Towards a national capability framework for Artificial Intelligence and Digital Medicine tools – A learning needs approach
|
Abdulhussein, Hatim
|
|
|
5 |
C |
p.
|
article
|
| 22 |
Towards early sepsis detection from measurements at the general ward through deep learning
|
Oei, Sebastiaan P.
|
|
|
5 |
C |
p.
|
article
|
Journal description