Latest AI and machine learning research in intensivists for healthcare professionals.
Effectively utilizing incomplete multi-modality data for diagnosis of Alzheimer's disease (AD) is st...
Machine learning approaches have been widely used for the identification of neuropathology from neur...
BACKGROUND: Hierarchical Multi-Label Classification is a classification task where the classes to be...
The aging population with its concomitant medical conditions, physical and cognitive impairments, at...
Simultaneous and proportional myocontrol of dexterous hand prostheses is to a large extent still an ...
Many biomedical classification problems are multi-label by nature, e.g., a gene involved in a variet...
To find genetic association between complex diseases and phenotypic traits, one important procedure ...
Many environmental incidents affect large areas, often in rough terrain constrained by natural obsta...
False arrhythmia alarms pose a major threat to the quality of care in today's ICU. Thus, the PhysioN...
This paper presents a novel approach for false alarm suppression using machine learning tools. It pr...
Hardware implementation of artificial neural networks facilitates real-time parallel processing of m...
The functional assessment of myoelectric control algorithms by persons with amputation promotes the ...
In this study, the heart rate variability (HRV) analysis is used to distinguish patients with systol...
Electronic Health Record (EHR) use in India is generally poor, and structured clinical information i...
Analytical and numerical methods have been used to extract essential engineering parameters such as ...
OBJECTIVE: To compare performance of risk prediction models for forecasting postoperative sepsis and...
Dynamic treatment regimes (DTRs) are sequential decision rules that focus simultaneously on treatmen...
Stereotactic radiosurgery (SRS) is the accurate, conformal delivery of high-dose radiation to well-d...
BACKGROUND: Many electronic infection detection systems employ dichotomous classification methods, c...
Personalization is the process of fitting a model to patient data, a critical step towards applicati...
Enzymes are important and effective biological catalyst proteins participating in almost all active ...