Prescriptions

New Insights Into Drug Repurposing for COVID-19 Using Deep Learning.

The coronavirus disease 2019 (COVID-19) has continued to spread worldwide since late 2019. To expedite the process of providing treatment to those who have contracted the disease and to ensure the accessibility of effective drugs, numerous strategies have been implemented to find potential anti-COVID-19 drugs in a short span of time. Motivated by this critical global challenge, in this review, we ...

From luxury to necessity: Progress of touchless interaction technology.

Touchless Technology is facilitating the move to Zero User Interface(UI) propelled by the COVID-19 pandemic which has accelerated the use of this technology due to hygiene requirements. Zero UI can be defined as a controlled interface that enables user interaction with technology through voice, gestures, hand interaction, eye tracking, and biometrics such as facial recognition and contactless fing...

Using predictive machine learning models for drug response simulation by calibrating patient-specific pathway signatures.

The utility of pathway signatures lies in their capability to determine whether a specific pathway or biological process is dysregulated in a given pa...

Enriching Human-Robot Interaction with Mobile App in Interventions of Children with Autism Spectrum Disorder.

: Autism spectrum disorder (ASD) is a group of complex lifelong neurodevelopmental disorders, characterized by difficulties in social communication an...

Artificial Neural Network Algorithms to Predict Resting Energy Expenditure in Critically Ill Children.

INTRODUCTION: Accurate assessment of resting energy expenditure (REE) can guide optimal nutritional prescription in critically ill children. Indirect ...

LGFC-CNN: Prediction of lncRNA-Protein Interactions by Using Multiple Types of Features through Deep Learning.

Long noncoding RNA (lncRNA) plays a crucial role in many critical biological processes and participates in complex human diseases through interaction ...

Artificial intelligence and machine learning approaches for drug design: challenges and opportunities for the pharmaceutical industries.

The global spread of COVID-19 has raised the importance of pharmaceutical drug development as intractable and hot research. Developing new drug molecu...

Efficient Prediction of Missed Clinical Appointment Using Machine Learning.

Public health and its related facilities are crucial for thriving cities and societies. The optimum utilization of health resources saves money and ti...

Deep Learning-Based Magnetic Resonance Imaging Features in Diagnosis of Perianal Abscess and Fistula Formation.

There was an investigation of the diagnostic and prognostic effect of magnetic resonance imaging (MRI) based on multimodal feature fusion algorithm fo...

Effect of Lamotrigine on Ouabain-Induced Arrhythmia in Isolated Atria of Guinea Pigs.

Lamotrigine (LTG) is an antiepileptic drug used in the treatment of seizures, mood disorders, and cognitive problems. The cardiac effects of LTG, suc...

Predicting obesity and smoking using medication data: A machine-learning approach.

PURPOSE: Administrative health datasets are widely used in public health research but often lack information about common confounders. We aimed to dev...

Deep learning for bone marrow cell detection and classification on whole-slide images.

Bone marrow (BM) examination is an essential step in both diagnosing and managing numerous hematologic disorders. BM nucleated differential count (NDC...

Towards better process management in wastewater treatment plants: Process analytics based on SHAP values for tree-based machine learning methods.

Understanding the mechanisms of pollutant removal in Wastewater Treatment Plants (WWTPs) is crucial for controlling effluent quality efficiently. Howe...

A Multitask Learning Model with Multiperspective Attention and Its Application in Recommendation.

Training models to predict click and order targets at the same time. For better user satisfaction and business effectiveness, multitask learning is on...

High alert drugs screening using gradient boosting classifier.

Prescription errors in high alert drugs (HAD), a group of drugs that have a high risk of complications and potential negative consequences, are a majo...

DeepCellState: An autoencoder-based framework for predicting cell type specific transcriptional states induced by drug treatment.

Drug treatment induces cell type specific transcriptional programs, and as the number of combinations of drugs and cell types grows, the cost for exha...

Modularity maximization as a flexible and generic framework for brain network exploratory analysis.

The modular structure of brain networks supports specialized information processing, complex dynamics, and cost-efficient spatial embedding. Inter-ind...

5FU-loaded PCL/Chitosan/FeO Core-Shell Nanofibers Structure: An Approach to Multi-Mode Anticancer System.

5-Fluorouracil (5FU) and FeO nanoparticles were encapsulated in core-shell polycaprolactone (PCL)/chitosan (CS) nanofibers as a multi-mode anticancer...

How adaptation, training, and customization contribute to benefits from exoskeleton assistance.

Exoskeletons can enhance human mobility, but we still know little about why they are effective. For example, we do not know the relative importance of...

Improving Human-Robot Interaction by Enhancing NAO Robot Awareness of Human Facial Expression.

An intriguing challenge in the human-robot interaction field is the prospect of endowing robots with emotional intelligence to make the interaction mo...