COVID-19

Associations Between Older Adults' Loneliness and Acceptance of Socially Assistive Robots: A Cross-Sectional Study.

The use of socially assistive robots (SARs) to enable older adults (aged ≥65 years) to live independently for as long as possible has been researched for several years. Of particular interest is the way SARs can combat loneliness. A quantitative cross-sectional study was conducted with 61 older adults in living facilities in Berlin, Germany. Paper-based questionnaires were used to elicit experienc...

Reverse tracking from drug-induced transcriptomes through multilayer molecular networks reveals hidden drug targets.

Identifying molecular targets of a drug is an essential process for drug discovery and development. The recent in-silico approaches are usually based on the structure information of chemicals and proteins. However, 3D structure information is hard to obtain and machine-learning methods using 2D structure suffer from data imbalance problem. Here, we present a reverse tracking method from genes to t...

A Systematic Review of Deep Learning Methodologies Used in the Drug Discovery Process with Emphasis on In Vivo Validation.

The discovery and development of new drugs are extremely long and costly processes. Recent progress in artificial intelligence has made a positive imp...

Weed Detection Using Deep Learning: A Systematic Literature Review.

Weeds are one of the most harmful agricultural pests that have a significant impact on crops. Weeds are responsible for higher production costs due to...

Benchmark methodological approach for the application of artificial intelligence to lung ultrasound data from COVID-19 patients: From frame to prognostic-level.

Automated ultrasound imaging assessment of the effect of CoronaVirus disease 2019 (COVID-19) on lungs has been investigated in various studies using a...

Applying T-classifier, binary classifiers, upon high-throughput TCR sequencing output to identify cytomegalovirus exposure history.

With the continuous development of information technology and the running speed of computers, the development of informatization has led to the genera...

Cell type-specific interpretation of noncoding variants using deep learning-based methods.

Interpretation of noncoding genomic variants is one of the most important challenges in human genetics. Machine learning methods have emerged recently...

Super High-Throughput Screening of Enzyme Variants by Spectral Graph Convolutional Neural Networks.

Finding new enzyme variants with the desired substrate scope requires screening through a large number of potential variants. In a typical enzyme eng...

Automatic implant shape design for minimally invasive repair of pectus excavatum using deep learning and shape registration.

Minimally invasive repair of pectus excavatum (MIRPE) is an effective method for correcting pectus excavatum (PE), a congenital chest wall deformity c...

Accurate Prediction of Transcriptional Activity of Single Missense Variants in HIV Tat with Deep Learning.

Tat is an essential gene for increasing the transcription of all HIV genes, and affects HIV replication, HIV exit from latency, and AIDS progression. ...

Robot-assisted pyeloplasty: How to deal with anatomic variants? A step-by-step video presentation.

INTRODUCTION: Pyeloplasty (open or Robot-assisted) is the gold standard of a symptomatic UPJ stenosis. Sometimes anatomic variants make the procedure ...

iQDeep: an integrated web server for protein scoring using multiscale deep learning models.

The remarkable recent advances in protein structure prediction have enabled computational modeling of protein structures with considerably higher accu...

A genome-wide association study of childhood adiposity and blood lipids.

The rising prevalence of childhood obesity and dyslipidaemia is a major public health concern due to its association with morbidity and mortality in ...

Review of Natural Language Processing in Pharmacology.

Natural language processing (NLP) is an area of artificial intelligence that applies information technologies to process the human language, understan...

Overall mortality risk analysis for rectal cancer using deep learning-based fuzzy systems.

Colorectal cancer is a leading cause of cancer mortality worldwide, with an increasing incidence rate in developing countries. Integration of genetic ...

Confused or not: decoding brain activity and recognizing confusion in reasoning learning using EEG.

Confusion is the primary epistemic emotion in the learning process, influencing students' engagement and whether they become frustrated or bored. Howe...

FDI and Wellbeing: A Key Node Analysis for Psychological Health in Response to COVID-19 Using Artificial Intelligence.

Developing countries are primary destinations for FDI from emerging economies following the World Investment Report 2022, including destinations in OE...

Deep Survival Analysis With Clinical Variables for COVID-19.

OBJECTIVE: Millions of people have been affected by coronavirus disease 2019 (COVID-19), which has caused millions of deaths around the world. Artific...

Beyond diagnosis: is there a role for radiomics in prostate cancer management?

The role of imaging in pretreatment staging and management of prostate cancer (PCa) is constantly evolving. In the last decade, there has been an ever...

The predictive model for COVID-19 pandemic plastic pollution by using deep learning method.

Pandemic plastics (e.g., masks, gloves, aprons, and sanitizer bottles) are global consequences of COVID-19 pandemic-infected waste, which has increase...