Understanding the data and reaching accurate conclusions are of paramount importance in
the present era of big data. Machine learning and probability theory methods have been …

Background: Digital clinical measures collected via various digital sensing technologies
such as smartphones, smartwatches, wearables, and ingestible and implantable sensors …

Inhaled oxygen, although commonly administered to patients with respiratory disease,
causes severe lung injury in animals and is associated with poor clinical outcomes in …

Purpose Acute respiratory distress syndrome (ARDS) is a serious respiratory condition with
high mortality and associated morbidity. The objective of this study is to develop and …

There is a growing gap between studies describing the capabilities of artificial intelligence
(AI) diagnostic systems using deep learning versus efforts to investigate how or when to …

Biomedical engineers prefer decision forests over traditional decision trees to design state-
of-the-art Parkinson's Detection Systems (PDS) on massive acoustic signal data. However …

Background and objective Acute respiratory distress syndrome (ARDS) is a life-threatening
pulmonary disease with a high clinical and cost burden across the globe. Artificial …

Background To develop and validate classifier models that could be used to identify patients
with a high percentage of potentially recruitable lung from readily available clinical data and …

Background: Clinical decision support (CDS) systems have emerged as tools providing
intelligent decision making to address challenges of critical care. CDS systems can be …

The integration of power line communications (PLC) and wireless communications in power
distribution internet of things (PD-IoT) provides a cost-efficient and easy-to-access solution …