COVID-19

Revealing Opinions for COVID-19 Questions Using a Context Retriever, Opinion Aggregator, and Question-Answering Model: Model Development Study.

BACKGROUND: COVID-19 has challenged global public health because it is highly contagious and can be lethal. Numerous ongoing and recently published studies about the disease have emerged. However, the research regarding COVID-19 is largely ongoing and inconclusive.

Older adults' experiences with and perceptions of the use of socially assistive robots in aged care: A systematic review of quantitative evidence.

BACKGROUND: Socially assistive robots (SARs) are created to meet challenges of the global increase of older adults. SARs are autonomous embodied technologies, equipped with auditory and visual faculties, enabling them to interact with users while performing assistive roles. Despite studies focusing on older adults' experiences with and perceptions of SARs, it remains unclear what these encompass.

Integrating human services and criminal justice data with claims data to predict risk of opioid overdose among Medicaid beneficiaries: A machine-learning approach.

Health system data incompletely capture the social risk factors for drug overdose. This study aimed to improve the accuracy of a machine-learning algo...

Socially Assistive Robots in Aged Care: Ethical Orientations Beyond the Care-Romantic and Technology-Deterministic Gaze.

Socially Assistive Robots (SARs) are increasingly conceived as applicable tools to be used in aged care. However, the use carries many negative and po...

Deep Learning Classification of Systemic Sclerosis Skin Using the MobileNetV2 Model.

Systemic sclerosis (SSc) is a rare autoimmune, systemic disease with prominent fibrosis of skin and internal organs. Early diagnosis of the disease i...

Role of Hybrid Deep Neural Networks (HDNNs), Computed Tomography, and Chest X-rays for the Detection of COVID-19.

COVID-19 syndrome has extensively escalated worldwide with the induction of the year 2020 and has resulted in the illness of millions of people. COVID...

Construction and validation of a machine learning-based nomogram: A tool to predict the risk of getting severe coronavirus disease 2019 (COVID-19).

BACKGROUND: Identifying patients who may develop severe coronavirus disease 2019 (COVID-19) will facilitate personalized treatment and optimize the di...

A deep learning method for HLA imputation and trans-ethnic MHC fine-mapping of type 1 diabetes.

Conventional human leukocyte antigen (HLA) imputation methods drop their performance for infrequent alleles, which is one of the factors that reduce t...

DeepTCR is a deep learning framework for revealing sequence concepts within T-cell repertoires.

Deep learning algorithms have been utilized to achieve enhanced performance in pattern-recognition tasks. The ability to learn complex patterns in dat...

Precision medicine and machine learning towards the prediction of the outcome of potential celiac disease.

Potential Celiac Patients (PCD) bear the Celiac Disease (CD) genetic predisposition, a significant production of antihuman transglutaminase antibodies...

Deep learning for diagnosis of COVID-19 using 3D CT scans.

A new pneumonia-type coronavirus, COVID-19, recently emerged in Wuhan, China. COVID-19 has subsequently infected many people and caused many deaths wo...

Machine Learning Analysis of Naïve B-Cell Receptor Repertoires Stratifies Celiac Disease Patients and Controls.

Celiac disease (CeD) is a common autoimmune disorder caused by an abnormal immune response to dietary gluten proteins. The disease has high heritabili...

Feasibility of ultraviolet light-emitting diode irradiation robot for terminal decontamination of coronavirus disease 2019 (COVID-19) patient rooms.

OBJECTIVE: To investigate the feasibility of using an ultraviolet light-emitting diode (UV LED) robot for the terminal decontamination of coronavirus ...

Machine Learning-Based Prediction of COVID-19 Severity and Progression to Critical Illness Using CT Imaging and Clinical Data.

OBJECTIVE: To develop a machine learning (ML) pipeline based on radiomics to predict Coronavirus Disease 2019 (COVID-19) severity and the future deter...

Reservoir hosts prediction for COVID-19 by hybrid transfer learning model.

The recent outbreak of COVID-19 has infected millions of people around the world, which is leading to the global emergency. In the event of the virus ...

Abnormal lung quantification in chest CT images of COVID-19 patients with deep learning and its application to severity prediction.

OBJECTIVE: Computed tomography (CT) provides rich diagnosis and severity information of COVID-19 in clinical practice. However, there is no computeriz...

A robust electrochemical immunosensor based on core-shell nanostructured silica-coated silver for cancer (carcinoembryonic-antigen-CEA) diagnosis.

This work addresses the fabrication of an efficient, novel, and economically viable immunosensing armamentarium that will detect the carcinoembryonic ...

Machine Learning Model for Computational Tracking and Forecasting the COVID-19 Dynamic Propagation.

A computational model with intelligent machine learning for analysis of epidemiological data, is proposed. The innovations of adopted methodology cons...

COVID-19 Recognition Using Ensemble-CNNs in Two New Chest X-ray Databases.

The recognition of COVID-19 infection from X-ray images is an emerging field in the learning and computer vision community. Despite the great efforts ...

Viral Pneumonia Screening on Chest X-Rays Using Confidence-Aware Anomaly Detection.

Clusters of viral pneumonia occurrences over a short period may be a harbinger of an outbreak or pandemic. Rapid and accurate detection of viral pneum...