BACKGROUND: Many individuals who will experience a first episode of psychosis (FEP) are not detected before occurrence, limiting the effect of preventive interventions. The combination of machine-learning methods and electronic health records (EHRs) ...
Intracellular transport is predominantly heterogeneous in both time and space, exhibiting varying non-Brownian behavior. Characterization of this movement through averaging methods over an ensemble of trajectories or over the course of a single traje...
One of the major challenges in robotics and engineering is to develop efficient technological solutions that are able to cope with complex environments and unpredictable constraints. Taking inspiration from natural organisms is a well-known approach ...
Nowadays, the focus on the development of assistive devices just for people with mobility disorders has shifted towards enhancing physical abilities of able-bodied humans. As a result, the interest in the design of cheap and soft wearable exoskeleton...
Risk stratification of young patients with hypertension remains challenging. Generally, machine learning (ML) is considered a promising alternative to traditional methods for clinical predictions because it is capable of processing large amounts of c...
In this paper, we have proposed a two-phase procedure (combining discrete graphs and wavelets) for constructing true epidemic growth. In the first phase, a graph-theory-based approach was developed to update partial data available and in the second p...
BACKGROUND: Many mortality prediction models have been developed for patients in intensive care units (ICUs); most are based on data available at ICU admission. We investigated whether machine learning methods using analyses of time-series data impro...
In this paper, we study the communication efficiency of a psychophysically tuned cascade of Wilson-Cowan and divisive normalization layers that simulate the retina-V1 pathway. This is the first analysis of Wilson-Cowan networks in terms of multivaria...
Early detection of breast cancer and its correct stage determination are important for prognosis and rendering appropriate personalized clinical treatment to breast cancer patients. However, despite considerable efforts and progress, there is a need ...
AMIA ... Annual Symposium proceedings. AMIA Symposium
Mar 4, 2020
Skin disease is a prevalent condition all over the world. Computer vision-based technology for automatic skin lesion classification holds great promise as an effective screening tool for early diagnosis. In this paper, we propose an accurate and inte...