Applications of machine learning to diagnosis and treatment of neurodegenerative diseases
MA Myszczynska, PN Ojamies, AMB Lacoste… - Nature reviews …, 2020 - nature.com
Globally, there is a huge unmet need for effective treatments for neurodegenerative
diseases. The complexity of the molecular mechanisms underlying neuronal degeneration …
diseases. The complexity of the molecular mechanisms underlying neuronal degeneration …
Application of artificial intelligence in surgery
Artificial intelligence (AI) is gradually changing the practice of surgery with technological
advancements in imaging, navigation, and robotic intervention. In this article, we review the …
advancements in imaging, navigation, and robotic intervention. In this article, we review the …
[HTML][HTML] Clinically applicable AI system for accurate diagnosis, quantitative measurements, and prognosis of COVID-19 pneumonia using computed tomography
Many COVID-19 patients infected by SARS-CoV-2 virus develop pneumonia (called novel
coronavirus pneumonia, NCP) and rapidly progress to respiratory failure. However, rapid …
coronavirus pneumonia, NCP) and rapidly progress to respiratory failure. However, rapid …
A weakly-supervised framework for COVID-19 classification and lesion localization from chest CT
Accurate and rapid diagnosis of COVID-19 suspected cases plays a crucial role in timely
quarantine and medical treatment. Developing a deep learning-based model for automatic …
quarantine and medical treatment. Developing a deep learning-based model for automatic …
Deep learning-based detection for COVID-19 from chest CT using weak label
Accurate and rapid diagnosis of COVID-19 suspected cases plays a crucial role in timely
quarantine and medical treatment. Developing a deep learning-based model for automatic …
quarantine and medical treatment. Developing a deep learning-based model for automatic …
No subclass left behind: Fine-grained robustness in coarse-grained classification problems
In real-world classification tasks, each class often comprises multiple finer-grained"
subclasses." As the subclass labels are frequently unavailable, models trained using only …
subclasses." As the subclass labels are frequently unavailable, models trained using only …
Hidden stratification causes clinically meaningful failures in machine learning for medical imaging
Machine learning models for medical image analysis often suffer from poor performance on
important subsets of a population that are not identified during training or testing. For …
important subsets of a population that are not identified during training or testing. For …
Attitudes and perceptions of UK medical students towards artificial intelligence and radiology: a multicentre survey
C Sit, R Srinivasan, A Amlani, K Muthuswamy… - Insights into …, 2020 - Springer
Objectives To explore the attitudes of United Kingdom (UK) medical students regarding
artificial intelligence (AI), their understanding, and career intention towards radiology. We …
artificial intelligence (AI), their understanding, and career intention towards radiology. We …
Notice of retraction: AI techniques for COVID-19
AA Hussain, O Bouachir, F Al-Turjman… - IEEE access, 2020 - ieeexplore.ieee.org
Notice of Retraction "AI Techniques for COVID-19," by Adedoyin Ahmed Hussain; Ouns
Bouachir; Fadi Al-Turjman; Moayad A Page 1 Notice of Retraction "AI Techniques for COVID-19," …
Bouachir; Fadi Al-Turjman; Moayad A Page 1 Notice of Retraction "AI Techniques for COVID-19," …
Deep-learning-assisted detection and segmentation of rib fractures from CT scans: Development and validation of FracNet
Background Diagnosis of rib fractures plays an important role in identifying trauma severity.
However, quickly and precisely identifying the rib fractures in a large number of CT images …
However, quickly and precisely identifying the rib fractures in a large number of CT images …