BACKGROUND: Modern molecular profiling techniques are yielding vast amounts of data from patient samples that could be utilized with machine learning methods to provide important biological insights and improvements in patient outcomes. Unsupervised ...
The increased availability of labeled X-ray image archives (e.g. ChestX-ray14 dataset) has triggered a growing interest in deep learning techniques. To provide better insight into the different approaches, and their applications to chest X-ray classi...
High-accuracy and fast detection of nutritive elements in traditional Chinese medicine (PN) is beneficial for providing useful assessment of the healthy alimentation and pharmaceutical value of PN herbs. Laser-induced breakdown spectroscopy (LIBS) w...
BMC medical informatics and decision making
Apr 4, 2019
BACKGROUND: A shareable repository of clinical notes is critical for advancing natural language processing (NLP) research, and therefore a goal of many NLP researchers is to create a shareable repository of clinical notes, that has breadth (from mult...
An ENsemble Deep Learning Optimal Treatment (EndLot) approach is proposed for personalized medicine problems. The statistical framework of the proposed method is based on the outcome weighted learning (OWL) framework which transforms the optimal deci...
BACKGROUND: Cryo-electron tomography (cryo-ET) enables the 3D visualization of cellular organization in near-native state which plays important roles in the field of structural cell biology. However, due to the low signal-to-noise ratio (SNR), large ...
UNLABELLED: Computational Intelligence Re-meets Medical Image Processing Analysis of Machine Learning Algorithms for Diagnosis of Diffuse Lung Diseases BACKGROUND: In the last decades, new optimization methods based on the nature's intelligence were...
Data are increasingly annotated with multiple ontologies to capture rich information about the features of the subject under investigation. Analysis may be performed over each ontology separately, but recently there has been a move to combine multipl...
Owing to improvements in image recognition via deep learning, machine-learning algorithms could eventually be applied to automated medical diagnoses that can guide clinical decision-making. However, these algorithms remain a 'black box' in terms of h...
AMIA ... Annual Symposium proceedings. AMIA Symposium
Dec 5, 2018
U.S. military veterans who were discharged from service for misconduct are at high risk for homelessness. Stratifying homelessness risk based on both military service factors and clinical characteristics could facilitate targeted provision of prevent...