OBJECTIVE: To evaluate the diagnostic accuracy of keratoconus using deep learning of the colour-coded maps measured with the swept-source anterior segment optical coherence tomography (AS-OCT).
International journal of medical informatics
Sep 23, 2019
INTRODUCTION: Depressive disorder is one of the major public health problems among the elderly. An effective depression risk prediction model can provide insights on the disease progression and potentially inform timely targeted interventions. Theref...
The path signature is a means of feature generation that can encode nonlinear interactions in data in addition to the usual linear terms. It provides interpretable features and its output is a fixed length vector irrespective of the number of input p...
Cardiovascular and interventional radiology
Sep 5, 2019
INTRODUCTION: To assess the performance of pre-ablation computed tomography texture features of adrenal metastases to predict post-treatment local progression and survival in patients who underwent ablation using machine learning as a prediction tool...
BACKGROUND: Predicting lung adenocarcinoma (LUAD) risk is crucial in determining further treatment strategies. Molecular biomarkers may improve risk stratification for LUAD.
Multiple sclerosis (MS) is the most common demyelinating disease. In MS, demyelination occurs in the white matter of the brain and in the spinal cord. It is thus essential to measure the tissue myelin content to understand the physiopathology of MS, ...
OBJECTIVE: To explore the value of radiomics features on non-contrast computed tomography (NCCT) in predicting early enlargement of spontaneous intracerebral hemorrhage (SICH).
Artificial intelligence (AI) is expected to support clinical judgement in medicine. We constructed a new predictive model for diabetic kidney diseases (DKD) using AI, processing natural language and longitudinal data with big data machine learning, b...
IEEE journal of biomedical and health informatics
Aug 1, 2019
Accurate assessment of pulmonary emphysema is crucial to assess disease severity and subtype, to monitor disease progression, and to predict lung cancer risk. However, visual assessment is time-consuming and subject to substantial inter-rater variabi...
BACKGROUND: The variation in articular cartilage thickness (ACT) in healthy knees is difficult to quantify and therefore poorly documented. Our aims are to (1) define how machine learning (ML) algorithms can automate the segmentation and measurement ...