Current challenges and future opportunities for XAI in machine learning-based clinical decision support systems: a systematic review
Machine Learning and Artificial Intelligence (AI) more broadly have great immediate and
future potential for transforming almost all aspects of medicine. However, in many …
future potential for transforming almost all aspects of medicine. However, in many …
Deep learning-enabled medical computer vision
A decade of unprecedented progress in artificial intelligence (AI) has demonstrated the
potential for many fields—including medicine—to benefit from the insights that AI techniques …
potential for many fields—including medicine—to benefit from the insights that AI techniques …
Automatic detection of 39 fundus diseases and conditions in retinal photographs using deep neural networks
LP Cen, J Ji, JW Lin, ST Ju, HJ Lin, TP Li… - Nature …, 2021 - nature.com
Retinal fundus diseases can lead to irreversible visual impairment without timely diagnoses
and appropriate treatments. Single disease-based deep learning algorithms had been …
and appropriate treatments. Single disease-based deep learning algorithms had been …
An ensemble of neural networks provides expert-level prenatal detection of complex congenital heart disease
R Arnaout, L Curran, Y Zhao, JC Levine, E Chinn… - Nature medicine, 2021 - nature.com
Congenital heart disease (CHD) is the most common birth defect. Fetal screening ultrasound
provides five views of the heart that together can detect 90% of complex CHD, but in …
provides five views of the heart that together can detect 90% of complex CHD, but in …
Medical imaging and nuclear medicine: a Lancet Oncology Commission
The diagnosis and treatment of patients with cancer requires access to imaging to ensure
accurate management decisions and optimal outcomes. Our global assessment of imaging …
accurate management decisions and optimal outcomes. Our global assessment of imaging …
Artificial intelligence and acute stroke imaging
JE Soun, DS Chow, M Nagamine… - American Journal …, 2021 - Am Soc Neuroradiology
Artificial intelligence technology is a rapidly expanding field with many applications in acute
stroke imaging, including ischemic and hemorrhage subtypes. Early identification of acute …
stroke imaging, including ischemic and hemorrhage subtypes. Early identification of acute …
Predicting treatment response from longitudinal images using multi-task deep learning
Radiographic imaging is routinely used to evaluate treatment response in solid tumors.
Current imaging response metrics do not reliably predict the underlying biological response …
Current imaging response metrics do not reliably predict the underlying biological response …
Federated learning improves site performance in multicenter deep learning without data sharing
Objective To demonstrate enabling multi-institutional training without centralizing or sharing
the underlying physical data via federated learning (FL). Materials and Methods Deep …
the underlying physical data via federated learning (FL). Materials and Methods Deep …
COVID-AL: The diagnosis of COVID-19 with deep active learning
The efficient diagnosis of COVID-19 plays a key role in preventing the spread of this
disease. The computer-aided diagnosis with deep learning methods can perform automatic …
disease. The computer-aided diagnosis with deep learning methods can perform automatic …
Machine learning in oral squamous cell carcinoma: Current status, clinical concerns and prospects for future—A systematic review
Background Oral cancer can show heterogenous patterns of behavior. For proper and
effective management of oral cancer, early diagnosis and accurate prediction of prognosis …
effective management of oral cancer, early diagnosis and accurate prediction of prognosis …