OBJECTIVE: The study objective was to generate a prediction model for treatment-resistant depression (TRD) using machine learning featuring a large set of 47 clinical and sociodemographic predictors of treatment outcome.
Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
Jan 1, 2018
The goals of this workshop are to discuss challenges in explainability of current Machine Leaning and Deep Analytics (MLDA) used in biocomputing and to start the discussion on ways to improve it. We define explainability in MLDA as easy to use inform...
Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
Jan 1, 2018
Survival prediction is very important in medical treatment. However, recent leading research is challenged by two factors: 1) the datasets usually come with multi-modality; and 2) sample sizes are relatively small. To solve the above challenges, we d...
Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
Jan 1, 2018
A central challenge of developing and evaluating artificial intelligence and machine learning methods for regression and classification is access to data that illuminates the strengths and weaknesses of different methods. Open data plays an important...
Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
Jan 1, 2018
Our knowledge of the biological mechanisms underlying complex human disease is largely incomplete. While Semantic Web technologies, such as the Web Ontology Language (OWL), provide powerful techniques for representing existing knowledge, well-establi...
Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
Jan 1, 2018
Electronic Health Records (EHRs) contain a wealth of patient data useful to biomedical researchers. At present, both the extraction of data and methods for analyses are frequently designed to work with a single snapshot of a patient's record. Health ...
Methods in molecular biology (Clifton, N.J.)
Jan 1, 2018
Robust high-content screening of visual cellular phenotypes has been enabled by automated microscopy and quantitative image analysis. The identification and removal of common image-based aberrations is critical to the screening workflow. Out-of-focus...
Annals of the American Thoracic Society
Jan 1, 2018
RATIONALE: Pediatric asthma has variable underlying inflammation and symptom control. Approaches to addressing this heterogeneity, such as clustering methods to find phenotypes and predict outcomes, have been investigated. However, clustering based o...
Journal of X-ray science and technology
Jan 1, 2018
The malignancy risk differentiation of pulmonary nodule is one of the most challenge tasks of computer-aided diagnosis (CADx). Most recently reported CADx methods or schemes based on texture and shape estimation have shown relatively satisfactory on ...
Computing and analyzing the neuronal structure is essential to studying connectome. Two important tasks for such analysis are finding the soma and constructing the neuronal structure. Finding the soma is considered more important because it is requir...
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.